U.S. patent application number 16/241936 was filed with the patent office on 2019-07-11 for systems and methods for interactive exercise therapy.
The applicant listed for this patent is Fitscript LLC. Invention is credited to Keivon Jones, Charles O'Connell, Matt Walton, Andrew Wood.
Application Number | 20190209777 16/241936 |
Document ID | / |
Family ID | 67140400 |
Filed Date | 2019-07-11 |
View All Diagrams
United States Patent
Application |
20190209777 |
Kind Code |
A1 |
O'Connell; Charles ; et
al. |
July 11, 2019 |
SYSTEMS AND METHODS FOR INTERACTIVE EXERCISE THERAPY
Abstract
Safe and effective exercise poses a specific set of challenges
for subjects diagnosed with diabetes. These challenges include the
coordination of exercise with blood glucose monitoring and insulin
administration. Failure to coordinate these factors effectively can
lead to various pathologies related to aberrant blood glucose
levels. Presented herein are methods, systems, algorithms, computer
program products, web portals, real-time live instruction, and
computer-executable code for exercise guidance and instruction
specific to diabetes relief and management. The systems as
disclosed herein can help ameliorate, slow, or reduce a likelihood
of developing a diabetic condition.
Inventors: |
O'Connell; Charles; (New
Haven, CT) ; Jones; Keivon; (Hamden, CT) ;
Walton; Matt; (New Haven, CT) ; Wood; Andrew;
(Bridgeport, CT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Fitscript LLC |
New Haven |
CT |
US |
|
|
Family ID: |
67140400 |
Appl. No.: |
16/241936 |
Filed: |
January 7, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62614782 |
Jan 8, 2018 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/14532 20130101;
A61M 2205/50 20130101; A63B 2230/202 20130101; A61M 2230/63
20130101; G06Q 30/0264 20130101; A61B 5/024 20130101; A61M 5/1723
20130101; G16H 40/67 20180101; A61M 2230/201 20130101; A61B 5/1128
20130101; A61B 5/4836 20130101; A61B 5/7275 20130101; A61B 2503/10
20130101; G16H 50/30 20180101; A61M 2205/3584 20130101; A63B
2230/04 20130101; G06Q 30/0269 20130101; A61B 5/743 20130101; A61M
2205/3553 20130101; A63B 24/0062 20130101; A63B 2024/0081 20130101;
G06Q 30/0251 20130101; G06Q 50/01 20130101; G16H 40/63 20180101;
A61B 5/00 20130101; A61B 5/0205 20130101; G16H 20/17 20180101; G16H
20/30 20180101; G06Q 30/0257 20130101; A61B 5/0002 20130101; A61B
5/4839 20130101 |
International
Class: |
A61M 5/172 20060101
A61M005/172; G06Q 30/02 20060101 G06Q030/02; G16H 20/30 20060101
G16H020/30; A61B 5/00 20060101 A61B005/00; A61B 5/0205 20060101
A61B005/0205; A63B 24/00 20060101 A63B024/00 |
Claims
1-90. (canceled)
91. A system comprising: a media device configured to present: a)
an instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) a non-exercise health recommendation based on the biometric
measurement detected in the subject.
92. The system of claim 91, further comprising a processor
configured to generate the non-exercise health recommendation based
on the biometric measurement detected in the subject, wherein the
processor is in communication with the media device.
93. The system of claim 92, further comprising a receiver
configured to receive the biometric measurement detected in the
subject, wherein the receiver is in communication with the media
device.
94. The system of claim 93, wherein the media device, the
processor, and the receiver are in a common housing.
95. The system of claim 93, wherein the media device, the
processor, the receiver, and the biometric device are in a common
housing.
96. The system of claim 91, wherein the biometric device is: a) in
communication with the media device; b) configured to detect the
biometric measurement in the subject; and c) configured to transmit
to the media device a reading of the biometric measurement detected
in the subject.
97. The system of claim 91, wherein the biometric device is a
glucose monitoring device and the biometric measurement detected in
the subject is a blood glucose level.
98. The system of claim 91, wherein the biometric device is a heart
rate monitoring device and the biometric measurement detected in
the subject is a heart rate.
99. A method comprising: a) receiving by a user from a media device
an instructional exercise electronic communication; b) performing
by the user an exercise provided by the instructional exercise
electronic communication; and c) receiving by the user from the
media device a non-exercise health recommendation based on a
biometric measurement detected in a user by a biometric device.
100. The method of claim 99, wherein the non-exercise health
recommendation is received when the biometric measurement detected
in the user is determined to be unsafe.
101. The method of claim 99, wherein the biometric device is a
glucose monitoring device and the biometric measurement detected in
the user is a blood glucose level.
102. The method of claim 99, wherein the biometric device is a
heart rate monitoring device and the biometric measurement detected
in the user is a heart rate.
103. The method of claim 102, wherein the non-exercise health
recommendation is received when the heart rate detected in the user
is determined to be in a zone from 40% to 100% of a maximum heart
rate in the user.
104. The method of claim 99, wherein the non-exercise health
recommendation is received during the performing of the exercise by
the user.
105. The method of claim 99, wherein the non-exercise health
recommendation is received before the performing of the exercise by
the user.
106. The method of claim 99, wherein the non-exercise health
recommendation is received after the performing of the exercise by
the user.
107. The method of claim 99, wherein the user is diabetic.
108. A method comprising: a) presenting by a media device to a
subject an instructional exercise electronic communication that
provides instruction for physical exercise based on a biometric
measurement detected in the subject by a biometric device; and b)
presenting by the media device to the subject an non-exercise
health recommendation based on the biometric measurement detected
in the subject.
109. The method of claim 108, further comprising detecting by the
biometric device the biometric measurement in the subject.
110. The method of claim 108, wherein the detecting of the
biometric measurement in the subject is during a state of physical
exercise.
Description
CROSS REFERENCE
[0001] This Application claims the benefit of U.S. Provisional
Application No. 62/614,782 filed Jan. 8, 2018, which is
incorporated herein by reference in its entirety.
BACKGROUND OF THE INVENTION
[0002] Safe and effective exercise poses a specific set of
challenges for subjects diagnosed with diabetes. These challenges
include the coordination of exercise with glucose monitoring and
administration of medications. Failure to coordinate these factors
effectively can lead to various pathologies, including headache,
seizure, faintness, withdrawal, depression, and hypoglycemia.
INCORPORATION BY REFERENCE
[0003] Each patent, publication, and non-patent literature cited in
the application is hereby incorporated by reference in its entirety
as if each was incorporated by reference individually.
SUMMARY OF THE INVENTION
[0004] In some embodiments, the invention provides a system
comprising: a media device configured to present: a) an
instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) an advertisement electronic communication based on the
biometric measurement detected in the subject.
[0005] In some embodiments, the invention provides a method
comprising: a) presenting by a media device to a subject an
instructional exercise electronic communication that provides
instruction for physical exercise based on a biometric measurement
detected in the subject by a biometric device; and b) presenting by
the media device to the subject an advertisement electronic
communication that provides an advertisement based on the biometric
measurement detected in the subject.
[0006] In some embodiments, the invention provides a computer
program product comprising a non-transitory computer-readable
medium having computer-executable code encoded therein, the
computer-executable code adapted to be executed to implement a
method of advertising to a subject, the method comprising: a)
processing an advertisement system, wherein the advertisement
system comprises: i) an instructional exercise communication
module; ii) an advertisement communication module; and iii) an
output module; b) generating by the instructional exercise
communication module an instructional exercise communication based
on a reading of a biometric measurement detected in the subject by
a biometric device; c) generating by the advertisement
communication module an advertisement based on the reading of the
biometric measurement detected in the subject; d) communicating by
the output module the instructional exercise communication to an
output media device; and e) communicating by the output module the
advertisement to the output media device.
[0007] In some embodiments, the invention provides a method
comprising: a) reviewing by a user from a media device an
instructional exercise electronic communication; b) performing by
the user an exercise suggested by the instructional exercise
electronic communication; and c) receiving by the user from the
media device an advertisement electronic communication that
provides an advertisement based on a biometric measurement detected
in the user by a biometric device.
[0008] In some embodiments, the invention provides a method
comprising: a) performing by a user an exercise; b) receiving by
the user from a media device an instructional exercise electronic
communication based on a biometric measurement detected in the user
by a biometric device; and c) receiving by the user from the media
device an advertisement electronic communication that provides an
advertisement based on the biometric measurement detected in the
user by the biometric device.
[0009] In some embodiments, the invention provides a system
comprising: a) a heart rate monitoring device configured to detect
a heart rate in a subject; and b) a media device configured to
present an advertisement electronic communication based on the
heart rate detected in the subject by the heart rate monitoring
device, wherein the heart rate monitoring device is configured to
transmit to the media device a reading of the heart rate in the
subject, wherein the media device is configured to present the
advertisement electronic communication upon determination that the
heart rate in the subject detected by the heart rate monitoring
device is in a zone from 40% to 100% of a maximum heart rate in the
subject.
[0010] In some embodiments, the invention provides a method
comprising presenting to a subject by a media device an
advertisement electronic communication that provides an
advertisement based on a heart rate detected in the subject by a
heart rate monitoring device, wherein the subject is performing an
exercise in a zone from 40% to 100% of a maximum heart rate in the
subject.
[0011] In some embodiments, the invention provides a computer
program product comprising a non-transitory computer-readable
medium having computer-executable code encoded therein, the
computer-executable code adapted to be executed to implement a
method of advertising to a subject, the method comprising: a)
processing an advertisement system, wherein the advertisement
system comprises: i) a biometric data receiving module; ii) an
advertisement communication module; and iii) an output module; b)
receiving by the biometric data receiving module a reading of a
heart rate detected in the subject by a heart rate monitoring
device and determining that the heart rate detected in the subject
is from 40% to 100% of a maximum heart rate in the subject; c)
generating by the advertisement communication module an
advertisement based on the reading of the heart rate detected in
the subject; and d) communicating by the output module the
advertisement to an output media device.
[0012] In some embodiments, the invention provides a method
comprising: a) reviewing by a user from a media device an
instructional exercise electronic communication; b) performing by
the user an exercise suggested by the instructional exercise
electronic communication; and c) receiving by the user from the
media device an advertisement electronic communication that
provides an advertisement upon determination that a heart rate in
the user detected by a heart rate monitoring device is in a zone
from 40% to 100% of a maximum heart rate in the user.
[0013] In some embodiments, the invention provides a system
comprising: a media device configured to present: a) an
instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) a clinical trial electronic communication based on the
biometric measurement detected in the subject.
[0014] In some embodiments, the invention provides a method
comprising: a) presenting by a media device to a subject an
instructional exercise electronic communication based on a
biometric measurement detected in the subject by a biometric
device; and b) determining eligibility of the subject in a clinical
trial based on the biometric measurement detected in the
subject.
[0015] In some embodiments, the invention provides a computer
program product comprising a non-transitory computer-readable
medium having computer-executable code encoded therein, the
computer-executable code adapted to be executed to implement a
method of recruiting a subject in a clinical trial, the method
comprising: a) processing a clinical trial recruitment system,
wherein the clinical trial recruitment system comprises: i) an
instructional exercise communication module; ii) an clinical trial
communication module; and iii) an output module; b) generating by
the instructional exercise communication module an instructional
exercise communication based on a reading of a biometric
measurement detected in the subject by a biometric device; c)
generating by the clinical trial communication module a clinical
trial electronic communication based on the reading of the
biometric measurement in the subject; d) communicating by the
output module the instructional exercise communication to an output
media device; and e) communicating by the output module the
clinical trial electronic communication to the output media
device.
[0016] In some embodiments, the invention provides a method
comprising: a) receiving by the user from a media device an
instructional exercise electronic communication; b) performing by
the user an exercise provided by the instructional exercise
electronic communication; and c) receiving by the user from the
media device a clinical trial communication that provides a
notification of a clinical trial based on a biometric measurement
in the user by a biometric device.
[0017] In some embodiments, the invention provides a system
comprising: a media device configured to present: a) an
instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) a non-exercise health recommendation to the subject based on
the biometric measurement detected in the subject.
[0018] In some embodiments, the invention provides a method
comprising: a) receiving by a user from a media device an
instructional exercise electronic communication; b) performing by
the user an exercise provided by the instructional exercise
electronic communication; and c) receiving by the user from the
media device a non-exercise health recommendation based on a
biometric measurement detected in a user by a biometric device.
BRIEF DESCRIPTION OF THE FIGURES
[0019] FIG. 1 illustrates an audiovisual data stream of the
interactive exercise program.
[0020] FIG. 2 illustrates an audiovisual data stream of the
interactive exercise program.
[0021] FIG. 3 illustrates a closed-loop system for insulin delivery
to a subject.
[0022] FIG. 4 illustrates a closed-loop system for insulin delivery
to a subject.
[0023] FIG. 5 depicts communications among components of a
closed-loop system.
[0024] FIG. 6 illustrates a computer system for facilitating
methods, systems, kits, or devices of the disclosure.
[0025] FIG. 7 depicts a live exercise monitoring system for the
online sharing of a real-time camera feed of a user.
[0026] FIG. 8 illustrates a graph of plasma glucose concentration
during aerobic exercise.
[0027] FIG. 9 illustrates a display of the interactive exercise
program.
[0028] FIG. 10 illustrates a display of the interactive exercise
program.
[0029] FIG. 11 illustrates a display of the interactive exercise
program.
[0030] FIG. 12 illustrates a display of the interactive exercise
program.
[0031] FIG. 13 illustrates a schematic of various factors
associated with diabetes management.
[0032] FIG. 14 illustrates a computer system for facilitating
methods, systems, kits, or devices of the disclosure.
[0033] FIG. 15 illustrates an audiovisual data stream of the
interactive exercise program.
[0034] FIG. 16 illustrates a computer system for facilitating
methods, systems, kits, or devices of the disclosure.
[0035] FIG. 17 illustrates an audiovisual data stream of the
interactive exercise program.
[0036] FIG. 18 illustrates a computer system for facilitating
methods, systems, kits, or devices of the disclosure.
DETAILED DESCRIPTION OF THE INVENTION
[0037] The disclosure provides methods, systems, algorithms,
computer programs, kits, devices, and computer-executable code for
exercise guidance and instruction specific to diabetes relief and
management, and the slowing or reducing a likelihood of developing
a diabetic condition. The methods, systems, algorithms, computer
programs, kits, devices, and computer-executable code are based in
part on correlations and interrelationships among variables
associated with glucose and insulin levels during exercise. The
systems include real-time access to online exercise portals and
communities. The portals can provide exercise instruction and
counseling and rescue from diabetic episodes that occur during
exercise. The portals also assist in avoiding such episodes. Live,
interactive online exercise is possible among a number of remote
users.
[0038] Effective diabetes management requires more than simply
modulation of blood glucose levels. Challenges related to diabetes
management can vary based on, for example, diabetes type, genetics,
diabetes comorbidities, lifestyle habits, fitness level, and
personality, which differ among individuals. Thus, diabetes
management systems are more effective when tailored to the specific
needs of an individual. The present disclosure provides dynamic and
comprehensive systems and methods of diagnosing and managing
diabetes in a subject by accounting for a variety of physiological
and psychological factors that contribute to the progression of
diabetes. The disclosed systems and methods can guide diabetics to
adhere to behavioral and long-term lifestyle habits for effective
diabetes management. As shown in FIG. 13, physiological and
psychological factors include, for example, emotional states,
community interactions, external environmental influences,
biometrics, nutrition, and medical interventions. Lifestyle factors
can further include, for example, sleeping habits and psychological
state.
[0039] The present disclosure further provides intelligent and
relevant real-time advertisement content to users based on the
various physiological and psychological factors.
Diabetes
[0040] In some embodiments, a subject using a method, system,
algorithm, computer program, kit, device, or computer-executable
code of the disclosure is diagnosed with diabetes. Non-limiting
examples of diabetes include diabetes mellitus, type-1 diabetes,
type-2 diabetes, prediabetes, gestational diabetes, latent
autoimmune diabetes of adults, congenital diabetes, cystic
fibrosis-related diabetes, steroid diabetes, and monogenic
diabetes.
[0041] Diabetes is a group of metabolic diseases in which high
blood sugar levels persist over a prolonged period. Symptoms of
high blood sugar include frequent urination, increased thirst, and
increased hunger. If left untreated, diabetes can cause many
complications. Acute complications include diabetic ketoacidosis
and non-ketotic hyperosmolar coma. Chronic complications include
cardiovascular disease, stroke, chronic kidney failure, foot
ulcers, and damage to the eyes.
[0042] Diabetes is caused by either failure of the pancreas to
produce sufficient insulin, or the cells of the body not responding
properly to the insulin produced. Type-1 diabetes results from the
inability of the pancreas to produce enough insulin. Type-2
diabetes begins with insulin resistance, a condition in which cells
and tissues fail to respond to insulin properly. As the disease
progresses, a lack of insulin can also develop. A primary cause is
excessive body weight and insufficient exercise. Gestational
diabetes is the third main form, and occurs when pregnant women
without a previous history of diabetes develop a high blood sugar
level.
[0043] Non-limiting examples of symptoms of diabetes include weight
loss, increased urination or polyuria, increased thirst or
polydipsia, increased hunger or polyphagia, blurry vision,
headache, fatigue, slow healing of cuts, itchy skin, changes in the
shape of the lens of the eye, and skin rashes or dermadromes. Low
blood sugar or hypoglycemia is prevalent in subjects with type-1
and type-2 diabetes. Non-limiting examples of hypoglycemic symptoms
include feelings of unease, sweating, trembling, increased
appetite, confusion, changes in behavior, seizures,
unconsciousness, and permanent brain damage. Subjects, such as
those diagnosed with type-1 diabetes, can also experience episodes
of diabetic ketoacidosis, a metabolic disturbance characterized by
nausea, vomiting and abdominal pain, the scent of acetone on the
breath, deep breathing known as Kussmaul breathing, and in severe
cases, reduced consciousness. Subjects, such as those diagnosed
with type-2 diabetes, can also experience a hyperosmolar
non-ketotic state, which is the result of dehydration.
[0044] Non-limiting examples of long-term complications due to
diabetes include damage to blood vessels, cardiovascular disease,
coronary artery disease, stroke, peripheral vascular disease, and
damage to blood vessels of the eyes, kidneys, and nerves. Damage to
blood vessels of the eyes, also known as diabetic retinopathy, can
result in gradual vision loss and blindness. Damage to blood
vessels of the kidneys, known as diabetic nephropathy, can result
in tissue scarring, urine protein loss, and eventually chronic
kidney disease. Damage to blood vessels of the nerves, known as
diabetic neuropathy, can result in numbness, tingling, pain,
altered pain sensation, leading to damage of the skin, and painful
muscle wasting and weakness. Diabetes-related foot problems, such
as diabetic foot ulcers, can occur and result in amputation.
[0045] Non-limiting examples of possible risks that can occur
during exercise include hypoglycemia, hyperglycemia, insulin shock,
diabetic shock, low heart rate, high heart rate, fainting,
unconsciousness, and death.
Co-Medications of Insulin and Diabetes Comorbidities
[0046] In some embodiments, the methods, systems, algorithms,
computer programs, kits, devices, and computer-executable code
include administration of an insulin. Non-limiting examples of
insulins include regular insulin, insulin glulisine, insulin
lispro, insulin aspart, insulin lispro protamine, insulin aspart
protamine, insulin neutral protamine Hagedorn (NPH), insulin
glargine, and insulin detemir. In some embodiments, the insulin is
a mixture of insulin. Non-limiting examples of mixtures of insulin
include about 30% regular insulin and about 70% insulin NPH; about
50% insulin lispro and about 50% insulin lispro protamine; about
25% insulin lispro and about 75% insulin lispro protamine; and
about 30% insulin aspart and about 70% insulin aspart
protamine.
[0047] In some embodiments, the methods, systems, algorithms,
computer programs, kits, devices, and computer-executable code
provided herein can incorporate information relating to a
medication taken by the subject that can alter how an exercise
instruction of the disclosure modulates blood sugar. Non-limiting
examples of medications include anti-diabetic medications, blood
pressure medications, anti-inflammatory medications, acid reflux
medications, and anti-arthritic medications. Non-limiting examples
of anti-diabetic medications include biguanides, sulfonylureas,
meglitinides, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4)
inhibitors, glucagon-like peptide-1 receptor (GLP-1) agonists,
sodium glucose co-transporter 2 (SGLT2) inhibitors, a-glucosidase
inhibitors, metformin, phenformin, buformin, rosiglitazone,
pioglitazone, troglitazone, canagliflozin, dapagliflozin, miglitol,
acarbose, voglibose, repaglinide, nateglinide, gliquidone,
glimepiride, gliclazide, glipizide, sitagliptin, liraglutide,
dulaglutide, and canagliflozin.
[0048] In some embodiments, the present invention includes systems
and methods for reducing an amount or dosage of a medication taken
by the subject based on user adherence to an exercise guidance
provided herein. Non-limiting examples of medications include
anti-diabetic drugs, blood pressure drugs, anti-inflammatory drugs,
acid reflux drugs, and anti-arthritic drugs. Non-limiting examples
of anti-diabetic drugs include insulins, DPP-4 inhibitors, GLP-1
agonists, SGLT2 inhibitors, a-glucosidase inhibitors, metformin,
phenformin, buformin, rosiglitazone, pioglitazone, troglitazone,
canagliflozin, dapagliflozin, miglitol, acarbose, voglibose,
repaglinide, nateglinide, gliquidone, glimepiride, gliclazide,
glipizide, sitagliptin, liraglutide, dulaglutide, and
canagliflozin.
[0049] In some embodiments, a subject of the disclosure engaging in
exercise exhibits comorbidities that, along with diabetes, can
affect how exercise modulates blood glucose. Non-limiting examples
of comorbidities include heart disease, respiratory disease,
hypertension, kidney problems, liver problems, strokes, and joint
disease.
[0050] Non-limiting examples of suitable variables include
established safety guidelines for glucose levels before during and
after exercise; time of day and duration of activity; heart rate
level and perceived exertion level; muscle fiber recruitment and
activity performed; presence of insulin and medication; and food
consumed.
[0051] Each variable can have a unique and distinguishable impact
on glucose levels during exercise. In some embodiments, based on
different implementations of combinations of the variables, the
disclosure can provide exercise recommendations and instruction
targeting specific and desired diabetes metrics outcomes.
Non-limiting examples of such outcomes include A1C reduction;
increase in insulin sensitivity; decrease in insulin resistance;
increased fat metabolism and weight loss; real-time reduction of
blood glucose levels; real-time elevation of blood glucose levels;
and reduction of anti-diabetic medication dependence. In some
embodiments, the disclosure can provide exercise recommendations
and instruction targeting specific and desired cardiovascular and
pulmonary outcomes. Non-limiting examples of such outcomes include
increased muscle tone; increased cardiac stress resistance; and
increased lung function.
Exercise Guidance Based Upon Target Heart Rates
[0052] In some embodiments, the methods of the disclosure are
adaptable and are designed to achieve specific outcomes related to
type-1 diabetes, such as reduced insulin dependence. In some
embodiments, the methods of the disclosure are adaptable and are
designed to achieve specific outcomes related to type-2 diabetes.
Non-limiting examples of such outcomes include A1C reduction;
increased fat metabolism; increased weight loss; real-time decrease
of blood glucose levels; increase in insulin sensitivity; and
decrease in insulin resistance.
[0053] In some embodiments, a collection of exercises is
pre-selected to achieve the desired diabetes metrics listed above.
Each suggested exercise is pre-selected to meet at least one of the
following criteria: be performed in a heart rate zone from 50% to
100% of a maximum heart rate and correlating exertion level that
does not cross the anaerobic threshold and does not stimulate the
raising of glucose levels; utilizes either aerobic glycolysis or
fat oxidization as the metabolic pathway for the provision of
energy; causes the systematic depletion of glycogen stores within
specific skeletal muscle without stimulating a glycolytic response
from the liver, such as release of stored glycogen into the blood
stream resulting in a rise in glucose levels, resulting in an
increase in insulin sensitivity and decrease in insulin resistance;
and be performed for an amount of time that stimulates the
systematic depletion of glycogen stores within selected skeletal
musculature.
[0054] Based on the subject's level of physical fitness, severity
of diabetic symptoms, and exercise preferences, the subject can
choose a target heart rate for an exercise session. The target
heart rate can be determined as a percentage of the subject's
maximum heart rate. The heart rate can also be chosen based on the
level of physical exertion that the subject chooses to experience.
Once the subject has chosen a target heart rate, the subject can
plan for the glucose and insulin levels that are suitable for the
target heart zone. The subject can thus establish target ranges or
target values for various biometric parameters, such as heart rate,
glucose level, and insulin level. The subject can also establish
rates of administration for insulin and glucagon.
[0055] For example, a subject can find that exercise that promotes
a heart rate of from 50% to 60% of the subject's maximum heart rate
is easy and comfortable. This heart rate can cause a small decrease
in glucose levels, as most of the subject's energy consumed is
carbohydrate. The subject should maintain a level of insulin that
is appropriate for the subject's carbohydrate consumption.
[0056] A subject can find that exercise that promotes a heart rate
of from 60% to 70% of the subject's maximum heart rate is
challenging and beneficial. This heart rate functions as a
fat-burning zone. Significant decreases in glucose levels are
possible. The subject should maintain a level of insulin that is
appropriate for the subject's carbohydrate consumption.
[0057] A subject can find that exercise that promotes a heart rate
of from 70% to 80% of the subject's maximum heart rate is hard. In
this zone, the subject's energy consumption is approximately half
carbohydrate and half fat. A subject can experience a risk of
hypoglycemia, and a significant drop in blood glucose levels is
possible. A subject can reduce insulin levels to aid in avoiding
hypoglycemia.
[0058] A subject can find that exercise that promotes a heart rate
of from 80% to 90% of the subject's maximum heart rate is very
hard. The subject's energy expenditure is approximately 85%
carbohydrate, 15% fat, and a small amount of protein. The subject's
glucose levels can fluctuate, and the ability to store and produce
glycogen can vary significantly based on physical fitness.
[0059] A subject can find that exercise that promotes a heart rate
of from 90% to 100% of the subject's maximum heart rate is the
subject's maximum possible effort. The subject's energy expenditure
is approximately 90% carbohydrate, 10% fat, and a small amount of
protein. The subject's glucose levels can rise, possibly to an
unsafe level, especially if the subject simultaneously consumes a
food containing a high carbohydrate content.
[0060] The maximum heart rate of the subject can be estimated in
several ways. In some embodiments, the maximum heart rate is
estimated by the following:
Maximum heart rate (in beats per minute [bpm])=220-(age of the
subject [age]);
[0061] In some embodiments, the maximum heart rate is estimated by
the following:
Maximum heart rate (in bpm)=208-(0.7.times.age);
[0062] In some embodiments, the maximum heart rate is estimated by
the following:
Maximum heart rate (in bpm)=207-(0.7.times.age);
[0063] In some embodiments, the maximum heart rate is estimated by
a treadmill test. The treadmill test entails a subject running on a
treadmill while connected to heart rate monitors and blood pressure
monitors. At various periods of time, the treadmill accelerates and
the incline rises, until the subject reaches the maximum sustained
effort. The measured heart rate of the subject at the maximum
sustained effort is the maximum heart rate of the subject.
[0064] Rather than choosing a target heart rate, a subject can also
choose a desired exercise to perform, and input the desired
exercise into any system herein. Based on the subject's choice of
exercise, and other factors, a system of the invention can approve,
disapprove, or modify the desired exercise. A system herein can
also modulate the subject's insulin administration rate or glucagon
administration rate based on choice of exercise; heart rate, for
example, real time heart rate as detected during exercise; glucose
level, for example, real time blood glucose level as detected
during exercise; or electronically-stored records of the subject's
past exercise performance and diabetes risk factors, such as
nutrition, time of day, and general level of physical fitness.
[0065] In some embodiments, prior to the subject being in a state
of physical exercise, while the subject is in a state of physical
rest, a heart rate of the subject at a resting level is from about
10% to about 50% of the maximum heart rate of the subject. In some
embodiments, the heart rate of the subject at the resting level is
from about 10% to about 15%, from about 15% to about 20%, from
about 20% to about 25%, from about 25% to about 30%, from about 30%
to about 35%, from about 35% to about 40%, from about 40% to about
45%, or from about 45% to about 50% of the maximum heart rate of
the subject.
[0066] In some embodiments, subsequent to the subject being in the
state of physical rest, while the subject is in the state of
physical exercise, the heart rate of the subject is elevated to an
active level that is from about 50% to about 100% of the maximum
heart rate of the subject. In some embodiments, the heart rate of
the subject is elevated to the active level that is from about 50%
to about 55%, from about 55% to about 60%, from about 60% to about
65%, from about 65% to about 70%, from about 70% to about 75%, from
about 75% to about 80%, from about 80% to about 85%, from about 85%
to about 90%, from about 90% to about 95%, or from about 95% to
about 100% of the maximum heart rate of the subject.
[0067] A subject can also approximate heart rate based on
comparison to a physical activity. A subject can plan to exercise
or perform a physical activity at a heart rate level that is
comparable to the heart rate experience, for example, during
walking, jogging, running, stair climbing, swimming, cycling,
golfing, dancing, stretching, or playing a sport. In some
embodiments, the exercise is aerobic exercise, endurance exercise,
muscle resistance training, or flexibility and balance
training.
[0068] In some embodiments, the subject receives or is administered
a dose of a hormone at a basal rate. Non-limiting examples of
hormones to be administered include insulin, glucagon, adrenaline,
and corticosteroids, such as cortisol. In some embodiments, the
basal rate of the dose of hormone is from about 2 units per day
(U/d) to about 50 U/d. In some embodiments, the basal rate of the
dose of hormone is from about 2 U/d to about 20 U/d, from about 5
U/d to about 50 U/d, from about 5 U/d to about 40 U/d, or from
about 10 U/d to about 50 U/d. In some embodiments, the basal rate
of the dose of hormone is from about 2 U/d to about 3 U/d, from
about 3 U/d to about 4 U/d, from about 4 U/d to about 5 U/d, from
about 5 U/d to about 6 U/d, from about 6 U/d to about 7 U/d, from
about 7 U/d to about 8 U/d, from about 8 U/d to about 9 U/d, from
about 9 U/d to about 10 U/d, from about 10 U/d to about 11 U/d,
from about 11 U/d to about 12 U/d, from about 12 U/d to about 13
U/d, from about 13 U/d to about 14 U/d, from about 14 U/d to about
15 U/d, from about 15 U/d to about 16 U/d, from about 16 U/d to
about 17 U/d, from about 17 U/d to about 18 U/d, from about 18 U/d
to about 19 U/d, from about 19 U/d to about 20 U/d, from about 20
U/d to about 21 U/d, from about 21 U/d to about 22 U/d, from about
22 U/d to about 23 U/d, from about 23 U/d to about 24 U/d, from
about 24 U/d to about 25 U/d, from about 25 U/d to about 26 U/d,
from about 26 U/d to about 27 U/d, from about 27 U/d to about 28
U/d, from about 28 U/d to about 29 U/d, from about 29 U/d to about
30 U/d, from about 30 U/d to about 31 U/d, from about 31 U/d to
about 32 U/d, from about 32 U/d to about 33 U/d, from about 33 U/d
to about 34 U/d, from about 34 U/d to about 35 U/d, from about 35
U/d to about 36 U/d, from about 36 U/d to about 37 U/d, from about
37 U/d to about 38 U/d, from about 38 U/d to about 39 U/d, from
about 39 U/d to about 40 U/d, from about 40 U/d to about 41 U/d,
from about 41 U/d to about 42 U/d, from about 42 U/d to about 43
U/d, from about 43 U/d to about 44 U/d, from about 44 U/d to about
45 U/d, from about 45 U/d to about 46 U/d, from about 46 U/d to
about 47 U/d, from about 47 U/d to about 48 U/d, from about 48 U/d
to about 49 U/d, or from about 49 U/d to about 50 U/d.
[0069] In some embodiments, the basal rate of the dose of hormone
is from about 0.05 units per hour (U/h) to about 2.2 U/h. In some
embodiments, the basal rate of the dose of hormone is from about
0.05 U/h to about 0.9 U/h, from about 0.2 U/h to about 2.2 U/h,
from about 0.2 U/h to about 1.8 U/h, or from about 0.3 U/h to about
2.2 U/h. In some embodiments, the basal rate of the dose of hormone
is from about 0.05 U/h to about 0.1 U/h, from about 0.1 U/h to
about 0.15 U/h, from about 0.15 U/h to about 0.2 U/h, from about
0.2 U/h to about 0.25 U/h, from about 0.25 U/h to about 0.3 U/h,
from about 0.3 U/h to about 0.35 U/h, from about 0.35 U/h to about
0.4 U/h, from about 0.4 U/h to about 0.45 U/h, from about 0.45 U/h
to about 0.5 U/h, from about 0.5 U/h to about 0.55 U/h, from about
0.55 U/h to about 0.6 U/h, from about 0.6 U/h to about 0.65 U/h,
from about 0.65 U/h to about 0.7 U/h, from about 0.7 U/h to about
0.75 U/h, from about 0.75 U/h to about 0.8 U/h, from about 0.8 U/h
to about 0.85 U/h, from about 0.85 U/h to about 0.9 U/h, from about
0.9 U/h to about 0.95 U/h, from about 0.95 U/h to about 1 U/h, from
about 1 U/h to about 1.05 U/h, from about 1.05 U/h to about 1.1
U/h, from about 1.1 U/h to about 1.15 U/h, from about 1.15 U/h to
about 1.2 U/h, from about 1.2 U/h to about 1.25 U/h, from about
1.25 U/h to about 1.3 U/h, from about 1.3 U/h to about 1.35 U/h,
from about 1.35 U/h to about 1.4 U/h, from about 1.4 U/h to about
1.45 U/h, from about 1.45 U/h to about 1.5 U/h, from about 1.5 U/h
to about 1.55 U/h, from about 1.55 U/h to about 1.6 U/h, from about
1.6 U/h to about 1.65 U/h, from about 1.65 U/h to about 1.7 U/h,
from about 1.7 U/h to about 1.75 U/h, from about 1.75 U/h to about
1.8 U/h, from about 1.8 U/h to about 1.85 U/h, from about 1.85 U/h
to about 1.9 U/h, from about 1.9 U/h to about 1.95 U/h, from about
1.95 U/h to about 2 U/h, from about 2 U/h to about 2.05 U/h, from
about 2.05 U/h to about 2.1 U/h, from about 2.1 U/h to about 2.15
U/h, or from about 2.15 U/h to about 2.2 U/h.
[0070] In some embodiments, the subject receives or is administered
the dose of hormone at an adjusted rate. The adjusted rate of the
dose of hormone is determined relative to the basal rate of the
dose of hormone. In some embodiments, the adjusted rate of the dose
of hormone is about 0.1%, about 0.5%, about 1%, about 5%, about
10%, about 15%, about 20%, about 25%, about 30%, about 35%, about
40%, about 45%, about 50%, about 55%, about 60%, about 65%, about
70%, about 75%, about 80%, about 85%, about 90%, about 91%, about
92%, about 93%, about 94%, about 95%, about 96%, about 9'7%, about
98%, about 99%, about 99.5%, about 99.9%, about 101%, about 105%,
about 110%, about 115%, about 120%, about 125%, about 130%, about
135%, about 140%, about 145%, about 150%, about 155%, about 160%,
about 165%, about 170%, about 175%, about 180%, about 185%, about
190%, about 195%, about 200%, about 250%, about 300%, about 350%,
about 400%, about 450%, about 500%, about 550%, about 600%, about
650%, about 700%, about 750%, about 800%, about 850%, about 900%,
about 950%, or about 1000% of the basal rate of the dose of
hormone.
[0071] In some embodiments, the adjusted rate of the dose of
hormone is from about 0.1% to about 0.5%, from about 0.5% to about
1%, from about 1% to about 5%, from about 5% to about 10 from about
10% to about 15%, from about 15% to about 20%, from about 20% to
about 25%, from about 25% to about 30%, from about 30% to about
35%, from about 35% to about 40%, from about 40% to about 45%, from
about 45% to about 50%, from about 50% to about 55%, from about 55%
to about 60%, from about 60% to about 65%, from about 65% to about
70%, from about 70% to about 75%, from about 75% to about 80%, from
about 80% to about 85%, from about 85% to about 90%, from about 90%
to about 91%, from about 91% to about 92%, from about 92% to about
93%, from about 93% to about 94%, from about 94% to about 95%, from
about 95% to about 96%, from about 96% to about 97%, from about 97%
to about 98%, from about 98% to about 99%, from about 99% to about
99.5%, from about 99.5% to about 99.9%, from about 101% to about
105%, from about 105% to about 110%, from about 110% to about 115%,
from about 115% to about 120%, from about 120% to about 125%, from
about 125% to about 130%, from about 130% to about 135%, from about
135% to about 140%, from about 140% to about 145%, from about 145%
to about 150%, from about 150% to about 155%, from about 155% to
about 160%, from about 160% to about 165%, from about 165% to about
170%, from about 170% to about 175%, from about 175% to about 180%,
from about 180% to about 185%, from about 185% to about 190%, from
about 190% to about 195%, from about 195% to about 200%, from about
200% to about 250%, from about 250% to about 300%, from about 300%
to about 350%, from about 350% to about 400%, from about 400% to
about 450%, from about 450% to about 500%, from about 500% to about
550%, from about 550% to about 600%, from about 600% to about 650%,
from about 650% to about 700%, from about 700% to about 750%, from
about 750% to about 800%, from about 800% to about 850%, from about
850% to about 900%, from about 900% to about 950%, or from about
950% to about 1000% of the basal rate of the dose of hormone.
[0072] In some embodiments, the adjusted rate of the dose of
insulin is about 15% of the basal rate of the dose of insulin, and
the heart rate of the subject is elevated to an active level that
is from about 50% to about 60% of the maximum heart rate of the
subject. In some embodiments, the adjusted rate of the dose of
insulin is about 15% of the basal rate of the dose of insulin, and
the heart rate of the subject is elevated to an active level that
is from about 60% to about 70% of the maximum heart rate of the
subject. In some embodiments, the adjusted rate of the dose of
insulin is about 50% of the basal rate of the dose of insulin, and
the heart rate of the subject is elevated to an active level that
is from about 70% to about 80% of the maximum heart rate of the
subject. In some embodiments, the adjusted rate of the dose of
insulin is about 85% of the basal rate of the dose of insulin, and
the heart rate of the subject is elevated to an active level that
is from about 80% to about 90% of the maximum heart rate of the
subject. In some embodiments, the adjusted rate of the dose of
insulin is about 90% of the basal rate of the dose of insulin, and
the heart rate of the subject is elevated to an active level that
is from about 90% to about 100% of the maximum heart rate of the
subject.
[0073] In some embodiments, the adjusted rate of the dose of
hormone is received by or administered to the subject for a time
period while the heart rate of the subject is at the resting level.
In some embodiments, the time period is at least about 5 minutes,
at least about 10 minutes, at least about 15 minutes, at least
about 20 minutes, at least about 25 minutes, at least about 30
minutes, at least about 35 minutes, at least about 40 minutes, at
least about 45 minutes, at least about 50 minutes, at least about
55 minutes, at least about one hour, at least about 90 minutes, at
least about two hours, at least about 150 minutes, at least about
three hours, at least about four hours, at least about five hours,
or at least about six hours.
[0074] In some embodiments, the time period is from about 5 minutes
to about 6 hours. In some embodiments, the time period is from
about 5 minutes to about 90 minutes. In some embodiments, the time
period is from about 5 minutes to about 10 minutes, from about 10
minutes to about 15 minutes, from about 15 minutes to about 20
minutes, from about 20 minutes to about 25 minutes, from about 25
minutes to about 30 minutes, from about 30 minutes to about 35
minutes, from about 35 minutes to about 40 minutes, from about 40
minutes to about 45 minutes, from about 45 minutes to about 50
minutes, from about 50 minutes to about 55 minutes, from about 55
minutes to about 60 minutes, from about 60 minutes to about 65
minutes, from about 65 minutes to about 70 minutes, from about 70
minutes to about 75 minutes, from about 75 minutes to about 80
minutes, from about 80 minutes to about 85 minutes, from about 85
minutes to about 90 minutes, from about 90 minutes to about 120
minutes, from about 120 minutes to about 150 minutes, from about
150 minutes to about 180 minutes, from about 180 minutes to about
240 minutes, from about 240 minutes to about 300 minutes, or from
about 300 minutes to about 360 minutes.
[0075] In some embodiments, the methods of the disclosure include
measuring the glucose level of the subject during the state of
physical exercise. In some embodiments, the glucose level measured
during the state of physical exercise is outside of a critical
glucose range. In some embodiments, the critical glucose range is
from about 70 mg/dL to about 250 mg/dL. In some embodiments, the
critical glucose range is from about 100 mg/dL to about 250 mg/dL.
In some embodiments, the critical glucose range is from about 70
mg/dL to about 140 mg/dL. In some embodiments, the critical glucose
range is from about 100 mg/dL to about 140 mg/dL. In some
embodiments, the critical glucose range is from about 70 mg/dL to
about 75 mg/dL, from about 75 mg/dL to about 80 mg/dL, from about
80 mg/dL to about 85 mg/dL, from about 85 mg/dL to about 90 mg/dL,
from about 90 mg/dL to about 95 mg/dL, from about 95 mg/dL to about
100 mg/dL, from about 100 mg/dL to about 105 mg/dL, from about 105
mg/dL to about 110 mg/dL, from about 110 mg/dL to about 115 mg/dL,
from about 115 mg/dL to about 120 mg/dL, from about 120 mg/dL to
about 125 mg/dL, from about 125 mg/dL to about 130 mg/dL, from
about 130 mg/dL to about 135 mg/dL, from about 135 mg/dL to about
140 mg/dL, from about 140 mg/dL to about 145 mg/dL, from about 145
mg/dL to about 150 mg/dL, from about 150 mg/dL to about 155 mg/dL,
from about 155 mg/dL to about 160 mg/dL, from about 160 mg/dL to
about 165 mg/dL, from about 165 mg/dL to about 170 mg/dL, from
about 170 mg/dL to about 175 mg/dL, from about 175 mg/dL to about
180 mg/dL, from about 180 mg/dL to about 185 mg/dL, from about 185
mg/dL to about 190 mg/dL, from about 190 mg/dL to about 195 mg/dL,
from about 195 mg/dL to about 200 mg/dL, from about 200 mg/dL to
about 205 mg/dL, from about 205 mg/dL to about 210 mg/dL, from
about 210 mg/dL to about 215 mg/dL, from about 215 mg/dL to about
220 mg/dL, from about 220 mg/dL to about 225 mg/dL, from about 225
mg/dL to about 230 mg/dL, from about 230 mg/dL to about 235 mg/dL,
from about 235 mg/dL to about 240 mg/dL, from about 240 mg/dL to
about 245 mg/dL, or from about 245 mg/dL to about 250 mg/dL.
[0076] In some embodiments, based upon a measurement of the glucose
level of the subject outside of the critical glucose range, an
action is performed to restore the glucose level to within the
critical glucose range. In some embodiments, the glucose level is
below the critical glucose range, and the action is the consumption
of a carbohydrate by the subject. Non-limiting examples of
carbohydrates include slow-acting carbohydrates, fast-acting
carbohydrates, chewable carbohydrates, dissolvable carbohydrates,
glucose carbohydrates, sucrose carbohydrates, and fructose
carbohydrates. In some embodiments, the glucose level is outside
the critical glucose range, and the action is the adjustment of the
dose of hormone to a second adjusted rate. In some embodiments, the
glucose level is outside of the critical glucose range, and the
action is a second state of physical exercise.
[0077] In some embodiments, the second adjusted rate of the dose of
hormone is determined relative to the adjusted rate of the dose of
hormone. In some embodiments, the second adjusted rate of the dose
of hormone is about 0.1%, about 0.5%, about 1%, about 5%, about
10%, about 15%, about 20%, about 25%, about 30%, about 35%, about
40%, about 45%, about 50%, about 55%, about 60%, about 65%, about
70%, about 75%, about 80%, about 85%, about 90%, about 91%, about
92%, about 93%, about 94%, about 95%, about 96%, about 97%, about
98%, about 99%, about 99.5%, about 99.9%, about 101%, about 105%,
about 110%, about 115%, about 120%, about 125%, about 130%, about
135%, about 140%, about 145%, about 150%, about 155%, about 160%,
about 165%, about 170%, about 175%, about 180%, about 185%, about
190%, about 195%, about 200%, about 250%, about 300%, about 350%,
about 400%, about 450%, about 500%, about 550%, about 600%, about
650%, about 700%, about 750%, about 800%, about 850%, about 900%,
about 950%, or about 1000% of the adjusted rate of the dose of
hormone.
[0078] In some embodiments, the second adjusted rate of the dose of
hormone is from about 0.1% to about 0.5%, from about 0.5% to about
1%, from about 1% to about 5%, from about 5% to about 10% from
about 10% to about 15%, from about 15% to about 20%, from about 20%
to about 25%, from about 25% to about 30%, from about 30% to about
35%, from about 35% to about 40%, from about 40% to about 45%, from
about 45% to about 50%, from about 50% to about 55%, from about 55%
to about 60%, from about 60% to about 65%, from about 65% to about
70%, from about 70% to about 75%, from about 75% to about 80%, from
about 80% to about 85%, from about 85% to about 90%, from about 90%
to about 91%, from about 91% to about 92%, from about 92% to about
93%, from about 93% to about 94%, from about 94% to about 95%, from
about 95% to about 96%, from about 96% to about 97%, from about 97%
to about 98%, from about 98% to about 99%, from about 99% to about
99.5%, from about 99.5% to about 99.9%, from about 101% to about
105%, from about 105% to about 110%, from about 110% to about 115%,
from about 115% to about 120%, from about 120% to about 125%, from
about 125% to about 130%, from about 130% to about 135%, from about
135% to about 140%, from about 140% to about 145%, from about 145%
to about 150%, from about 150% to about 155%, from about 155% to
about 160%, from about 160% to about 165%, from about 165% to about
170%, from about 170% to about 175%, from about 175% to about 180%,
from about 180% to about 185%, from about 185% to about 190%, from
about 190% to about 195%, from about 195% to about 200%, from about
200% to about 250%, from about 250% to about 300%, from about 300%
to about 350%, from about 350% to about 400%, from about 400% to
about 450%, from about 450% to about 500%, from about 500% to about
550%, from about 550% to about 600%, from about 600% to about 650%,
from about 650% to about 700%, from about 700% to about 750%, from
about 750% to about 800%, from about 800% to about 850%, from about
850% to about 900%, from about 900% to about 950%, or from about
950% to about 1000% of the adjusted rate of the dose of
hormone.
[0079] In some embodiments, subsequent to the subject being in the
state of physical exercise, while the subject is in the second
state of physical exercise, the heart rate of the subject is
modified to a second active level that is from about 50% to about
100% of the maximum heart rate of the subject. In some embodiments,
the heart rate of the subject is elevated to the active level that
is from about 50% to about 55%, from about 55% to about 60%, from
about 60% to about 65%, from about 65% to about 70%, from about 70%
to about 75%, from about 75% to about 80%, from about 80% to about
85%, from about 85% to about 90%, from about 90% to about 95%, or
from about 95% to about 100% of the maximum heart rate of the
subject.
[0080] In some embodiments, the glucose level of the subject during
the state of physical exercise is above the critical glucose range
and the heart rate of the subject is modified to the second active
level that is from about 50% to about 60%, from about 60% to about
70%, or from about 70% to about 80% of the maximum heart rate of
the subject. In some embodiments, the glucose level of the subject
during the state of physical exercise is below the critical glucose
range and the heart rate of the subject is modified to the second
active level that is from about 90% to about 100% of the maximum
heart rate of the subject.
[0081] In some embodiments, an exercise instruction of the
disclosure is based upon a time of day. Non-limiting examples of
times of day include early morning, mid-morning, afternoon, and
evening. In some embodiments, the exercise instruction of the
disclosure is based upon a diet consumed by the subject. In some
embodiments, the exercise instruction of the disclosure is based
upon an activity of the state of physical exercise. In some
embodiments, the activity lowers the glucose level of the subject.
In some embodiments, the activity raises the glucose level of the
subject. If the subject chooses and exercise to perform, the system
can modify the subject's insulin or glucagon administration rate
based on the time of day, the selection of exercise, and other
factors, such as heart rate and glucose levels.
Media-Enhanced Exercise Instruction
[0082] A subject can receive exercise instruction for safe and
effective activities for a diabetic. The subject can receive
exercise instruction while using any device or system herein, or
can receive exercise instruction without using any such device or
system. Exercise instruction can be presented to the subject in any
suitable format, for example, video, audio, email, text, in-person,
presentation of words associated with an exercise instruction,
presentation of sounds or symbols associated with an exercise
instruction, group, one-on-one, and any combination thereof.
Devices suitable for presenting exercise instruction include a
media device, a communication medium, a video display device or
unit, an audio device or unit, immersive virtual reality device, a
hologram or holographic display medium, a device suitable for
conveyance of email or text message, such as a computer, cellular
telephone, or tablet, mannequins, posters, flyers, and any
combination of the foregoing. In some embodiments, the subject
inputs into the system a choice of exercise to perform, and
receives instruction based on the subject's choice of exercise.
[0083] FIG. 1 illustrates an example video display for exercise
instruction 100. The video for exercise instruction 100 comprises
multimedia video content featuring exercise instruction and
correlating presentation of diabetes metrics 101, including
suggested heart rate zone 102, suggested perceived exertion rate
103, suggested glycogen depletion rate 104, potential blood glucose
impact 105, suggested skeletal muscle usage 106, suggested
metabolic pathway 107, amount of time per exercise 108, and name of
exercise performed 109.
[0084] Video instruction for each exercise is presented on an
electronic device to the subject in real time, and the subject can
participate by performing or learning the exercise. Non-limiting
examples of electronic devices include displays, computers,
televisions, projectors, smartphones, smart watches, tablets, and
electronic glasses. As the video for exercise instruction proceeds,
and the instructor progresses through a series of exercises,
information is displayed on the video output. Each exercise
instruction is accompanied by the provision of suggested
information related to desired results illustrated as side bars and
popups in the video for exercise instruction.
[0085] FIG. 2 illustrates an example video display for exercise
instruction 200. The video for exercise instruction 200 comprises:
multimedia video content featuring exercise instruction integrating
content with software and devices that track biometric data related
to diabetes and health metrics in real time. In this embodiment,
the video for exercise instruction 200 combines the presentation of
suggested data and information with the presentation of diabetes
metrics 201 integrating real-time biometric data, including active
heart rate 202, suggested glycogen depletion rate 203, blood
glucose level 204, suggested skeletal muscle usage 205, calorie
expenditure and geospatial distance covered 206, amount of time per
exercise 207, and name of exercise performed 208.
[0086] Biometric data can be incorporated and derived from software
and wearable biometric tracking devices, sensing and image analysis
data obtained from cameras on a smartphone or telecommunications
device, sensing and image analysis data obtained from external
cameras, including visible spectrum and infrared cameras, and
smartphone applications that track distance, speed, time and
geography covered. These devices are worn by the subject, and
monitor the signals of the subject. Data collected from these
devices are transmitted to the system of the invention, which
processes the data to provide a real-time display of data generated
from the subject. The subject thus has the opportunity to observe
and evaluate performance and compare output to recommended
standards. The data can replace or supplement the suggested data,
and are displayed in real time through Application Program
Interface (API) protocols and BlueTooth.RTM. integration.
[0087] Non-limiting examples of potential biometric data and
smartphone application information include information derived from
heart rate monitoring devices; information derived from external
hormone delivery devices, such as insulin pumps and glucagon pumps;
information derived from continuous glucose monitoring (CGM)
devices; information derived from non-continuous glucose monitoring
devices, such as blood glucose meters (BGMs); information derived
from calorie expenditure devices; information derived from step
counters; information derived from time and clock applications;
information derived from metabolic pathway devices, such as New
Leaf.TM. technology; and information derived from distance, speed
and geospatial distance tracking devices, such as GPS
technology.
[0088] In some embodiments, the disclosure herein provides methods
for suggestive and responsive multimedia exercise instruction
featuring, for example, a smartphone application that integrates
exercise instruction and video content with biometric software and
devices to make exercise suggestions based on desired diabetes
metrics outcomes. Non-limiting examples of such outcomes include
A1C reduction; A1C goal; increase in insulin sensitivity; decrease
in insulin resistance; fat metabolism and weight loss; real-time
lowering of blood glucose levels; real-time elevation of blood
glucose levels; and reduction of anti-diabetic medication
usage.
[0089] Utilizing the software, protocols, and algorithms described
above, an application makes exercise suggestions based on factors
geared towards exercise effective for a diabetes patient.
Non-limiting examples of such factors include pre-exercise glucose
levels; information derived from individual diabetes profile;
established safety guidelines related to comorbidity conditions;
real-time feedback from biometric devices; algorithms described
herein; and categorization of exercise routines correlated with
specific diabetes outcomes and conditions.
[0090] FIG. 8 provides a graphical depiction of average plasma
(blood) glucose level in millimolar (mM) over a period of exercise
time in minutes (min) in individuals consuming either placebo
(diamonds) or glucose polymer (circles) during prolonged,
high-intensity aerobic exercise. Using the methods, systems,
algorithms, computer program products, and computer-executable code
of the disclosure for exercise guidance, blood glucose levels can
be monitored over an exercise time course.
[0091] In some embodiments, an application platform disclosed
herein provides a portal for subjects and providers to: input
diabetes-specific biometric data such as glucose level, heart rate
level and medication, such as manually via a smartphone
application; receive specific and responsive exercise guidance
based upon real-time data entry of diabetes-related biometric data,
utilizing the clinical algorithms for exercise therapy; offer care
providers a structured exercise program that can be both prescribed
and reviewed; and integrate the algorithms and apps with wearable
devices, biometric monitoring devices, and drug delivery devices to
automate the input of diabetes-related biometric data and provide
responsive exercise suggestions, based on the real-time flow of
automated data.
[0092] The subject can have target ranges for various parameters,
including biometric parameters and device parameters, such as
dosage rates for insulin and glycogen administration devices. The
target parameters can be pre-determined, prescribed, or determined
by the subject, a health care professional, or a fitness
professional. The system can alert the subject when a parameter
deviates from a target range, for example, by audio, video, text,
email, or by shutting down the exercise instruction program. The
system can also modify the exercise program to instruct the subject
to undertake activities likely to adjust the parameter back to the
target range.
Interactive Safety Monitoring
[0093] During exercise, user biometrics can be assessed in
real-time to provide actionable advice to a user when the system
detects measurements that suggest medical danger.
[0094] For example, when fasting blood glucose levels increase to
about 240-300 mg/dL, the user can be alerted of dangerously high
blood sugar. The user can be advised to administer insulin to
reduce glucose levels. When blood glucose levels exceed 300 mg/dL,
the system can automatically connect the user with a health care
professional. Alternatively, when fasting blood glucose levels
decrease to about 70-90 mg/dL the user can be alerted of
dangerously low blood sugar, and can be advised to intake sugar
immediately to normalize blood glucose levels.
[0095] Relative rates of biometrics variables can also suggest
whether medical attention is needed. Detection of dangerous
relative rates of biometrics can trigger automated alerts to and/or
connection with an authorized diabetes professional (e.g., a
doctor, nurse, or certified diabetes educator), caregiver, or
entity. In addition to absolute biometric measurements, the system
can detect biometric rates and fluctuations. Relative rates of
biometrics variables can also suggest whether medical attention is
needed.
[0096] Biometrics can include, for example, heart rate, glucose
levels, time of day, diet, medications, and exercise type. In some
embodiments, biometric variables can include genomic data of the
user.
Fully-Monitored Experience
[0097] In some embodiments, the system can provide a
fully-monitored experience to a user. Tier 1: a virtual support
team and the user can interact with one another. For example, a
user can communicate a question, concern, or comment to a support
team member. User/support interactions can be facilitated through
an instant messaging interface, a video conference, or a phone
call. Tier 2: the system can identify a condition based on user
biometrics and automatically perform an action to modify or correct
that biometric of the user. The action can include, for example,
alerting the user through a visual or audio notification to adjust
an insulin dosage, adjustment of an insulin dosage, adjustment of a
glucagon dosage, and adjustment of an exercise regimen. A user
alert can include a recommendation to slow performance of an
exercise, a recommendation to stop performance of an exercise, a
recommendation to adjust insulin dosage, and a recommendation to
consume food or beverage. For example, the system can detect very
high glucose levels that suggest that the user is experiencing
hyperglycemia. The system can automatically increase or decrease
the user's insulin dosage. Tier 3: the system can provide access to
human interaction to the user. For example, the system can connect
the user to a health professional when the system detects unsafe or
abnormal conditions. These conditions can include glucose levels
have not been correctable after multiple attempts and exercise
levels are detected to be unsafe.
Live Trainer Exercise Instruction
[0098] In some embodiments, the recommended exercises can be
broadcast live from a remote location. Live broadcast provides a
real-time video and audio stream of an exercise routine with a
real-life trainer. Live broadcast can include multiple daily
classes that can be streamed to users worldwide. Live exercise
routines or classes can vary in style and difficulty depending on
user biometrics.
[0099] Users can interact with a live, digital trainer in
real-time. Users and digital coaches can interact through
bi-directional communications. Digital trainers can receive user
data from logged users and send information to users. User data can
include biometric data and other user identification information.
Accordingly, digital trainers can provide personalized guidance and
feedback in real-time. Live broadcast can help facilitate user
compliance and engagement. A digital trainer can be a fitness
professional, physical therapist, or health care professional.
[0100] In addition to live interactions with the digital trainer,
users can interact with other users. Users can share experiences
and advice with one another to foster a supportive community.
[0101] In some embodiments, the system provides a merit-based
rewards system to further promote user engagement. For example, the
system can monitor daily activity of the user and distribute
points.
[0102] The system can operate through and/or facilitate machine
learning, deep learning, and other neural networks. Thus,
prediction factors grow as the system collects more data from a
wider range of users. For example, glucose level and other
biometrics of a user can be input into the system. Biometrics input
can be manually inputted by the user or automatically inputted
through a user monitoring device. The system can determine whether
the user can safely perform exercises. The system can recommend
video content of exercises in real-time based on user biometrics
and fluctuations thereof. The system can provide live video and
audio programming based on user biometrics and fluctuations
thereof. Video programming can change based on user selection and
biometric measurements during exercise.
[0103] FIG. 7 illustrates an example of a live exercise monitoring
system 700. The live exercise counseling can be based, for example,
on a camera feed 701 that films a person performing the exercise.
As illustrated in FIG. 7, the camera feed 701 can be processed by a
server 702 that is onsite at the point of exercise. Open broadcast
software can be used to make the camera feed 701 available to a web
service provider. The web service provider can encode the camera
stream, and distribute the stream to users 705 of the system using
open broadcast software 703 and a web service provider 704. Users
can receive the live camera feed on a telecommunications device,
for example, a smartphone a cellular telephone, a computer, or any
web-access display, to view the camera feed. The user 705 can then
view the live exercise in real time. In some embodiments, external
cameras can be used to capture the user's image for video
production, broadcast, image analysis, or uni-directional and
bi-directional communication. Image analysis can refer to the
analysis of user images captured by cameras using automated
assessment tools, screened and interpreted using human experts
and/or artificial intelligence to identify a broad range of
physiological, behavioral, or environmental patterns. Non-limiting
examples of image patterns include changes in the user's facial
complexion (flush or paleness), body posture, facial expression,
respiration, perspiration, body temperature, and performance of
correct or incorrect movements.
[0104] The process can work, for example, bi-directionally. In one
direction, the exerciser who is filmed on the live camera feed 701
can be an instructor, whose exercise is being broadcast to users
who receive an instructional exercise feed. In the reverse
direction, the exerciser can be a subscriber who is in need of
exercise coaching, therapy, monitoring, or risk management for
diabetic episodes. The recipient or user 705 of the camera feed 701
can be an exercise professional who provides guidance, instruction,
and if necessary, rescue instruction in the exerciser becomes at
risk of a diabetic episode. Such a risk can be monitored and
reported by a biometric device, worn by the exerciser, which feeds
into the system.
[0105] Users of the system 700 can access an online portal, for
example, through a check-in module. Once checked in, the system 700
can monitor the presence of the user, provide the user with a
messaging platform, and provide access to automated events through
a central processing unit (CPU) 707. The messaging platform can be
used for messaging with other users, members of an on-line
community, exercise instructors, health care providers, payers,
pharmaceutical companies, research entities, IT support
specialists, and emergency services. Non-limiting examples of
automated events include exercise sessions, the sending or
receiving of instructional material, nourishment, checking
biometric signals such as heart rate and blood sugar, reminders,
and journal entries.
[0106] System 700 illustrated in FIG. 7 is scalable. The system can
support an individual subscriber, a population of subscribers, an
individual exercise instructor, a population of exercise
instructors, and any number of participants, specialists, health
care providers, payers, pharmaceutical companies, research
entities, IT support specialists, and users of any type.
Online Portal for Exercise Instruction
[0107] The system can provide an online portal through which users
and subscribers can receive exercise instruction. The online portal
can provide example exercises, recommended exercises, recommended
food and drink, recommended routines, time of day to exercise, and
any other information useful for guiding the exercise program. The
portal can provide instruction through various media. Instruction
can be through images, pictures, photographs, video clips,
cartoons, voice, or audio instruction of exercise. The instructions
can be designed to be used during exercise, in preparation for
exercise, or for future advice.
[0108] In some embodiments, the online portal can provide live
exercise instruction from a human instructor. For example, live
exercise instructions can be offered daily, weekly, bi-weekly, or
monthly.
[0109] A user can access the online portal through a log in. Once
logged in, the user can access various personalized features, for
example, a calendar, a schedule, list of preferred exercises, a
community of participants, a journal, dietary advice, health
quizzes, reward programs, a progress report, a history of past
exercises, and a history of diabetic episodes. The user can access
these features to provide a customized exercise environment.
[0110] In some embodiments, the online portal can access any
biometric equipment attached to the user, such as a heart rate
monitor and a glucose meter. The portal can read the biometric
devices and display the readings to the user. The portal can also
search a database of exercise and diabetes resources in real time
to determine options for the user and possible risks. For example,
the portal can identify that the user should change the current
exercise based on biometric readings. The portal can suggest a
different, safer exercise based on the readings. In some
embodiments, the user has the option to browse a list of exercises
that the portal identifies as safe for the current biometric
readings. The user can scroll, swipe, or otherwise browse exercise
alternatives to choose one to perform.
[0111] Upon choosing an exercise, the user can access instruction
information. For example, the user can watch a video that
illustrates proper exercise form. The user can also access
information about the exercise itself, and any risks associated
with the exercise.
[0112] In some embodiments, the online portal connects the user to
a monitoring system. The monitoring system can be automated, or
staffed by health care or exercise specialists. The monitoring
system can identify changes in biometric parameters during use, and
identify readings that are safe, effective, or risky. The portal
can notify the user of the finding. When the readings show risk,
the system can intervene to attenuate the risk. An automated system
can automatically send intervention instructions to the user upon
determining the risk. A staffed system can allow a specialist to
analyze the information and determine an intervention for the user
based on sound professional judgement. The intervention can be, for
example, a change in exercise, a change of the pace of exercise,
stopping exercise, drinking water, eating or drinking a sugary
food, or activating a rescue device, such as an insulin or glucagon
pump.
Augmented Reality
[0113] The system can provide an augmented (virtual) reality to
create a gamified interface for users. The invention includes
systems and methods for regulating and scoring user exercise
milestones in a virtual reality game. For example, users can walk,
run, ride a bicycle, or perform other movement-based exercises in a
virtual landscape alongside other users. The virtual landscape can
be a location-based parallel reality. The virtual landscape can
change during the course of the exercise. For example, users can be
advised to complete a virtual obstacle course while performing an
exercise. The obstacle course can vary in location, landscape, and
difficulty. In some embodiments, users can interact with other
users based on detected user locations. A fully-immersive,
interactive experience provided by the system can provide further
incentive to comply with exercise recommendations.
[0114] The location-based parallel reality hosted by a game server
can include a virtual gaming environment with geography that
parallels real world geography. Users or players can engage in
movement-based exercises while navigating through a range of
coordinates that correspond to geographic space in the real world.
Accordingly, users can be monitored or tracked using location-based
position-tracking systems (e.g. GPS) associated with a user's
mobile device.
[0115] In some embodiments, the system can monitor user progress
including, for example, pace, distance, elevation, heart rate,
glucose level, and insulin level. The system can generate
personalized exercise plans for users based on user-inputted
personal goals, user biometrics, and fitness level. In some
embodiments, users can compare their progress with that of other
users and compete with friends or fellow users.
[0116] In some embodiments, the system can provide personalized
music playlists, Podcasts, or audio support or guidance while a
user is performing an exercise.
[0117] The navigational medium can be based on user biometrics.
User biometrics can be measured to predict and recommend different
types of exercises to a user. For example, a user can be performing
a running exercise in an augmented reality landscape and
experiences a trending pattern of blood glucose readings (e.g., up
or down at different rates of change) from a continuous blood
glucose monitor. The landscape of the augmented reality of the user
can change to increase or decrease the level of effort for
navigation depending on the desired impact on the trending blood
glucose level.
[0118] Exercise recommendations can be automatically displayed
after user biometrics are detected. Biometrics can include, for
example, heart rate, glucose levels, time of day, diet,
medications, and exercise. In some embodiments, biometric variables
can include genomic data of the user.
Targeted Advertising Based on Biometric Data
[0119] Biometric data can provide valuable information about a
user's health and lifestyle, which can be associated with a product
or service in the form of an advertisement. Instead of random
presentation of advertising and retail information to a user, an
advertiser can more effectively connect with a user by targeting a
particular user demographic by monitoring and analyzing user
biometrics. Target advertising increases the likelihood of a user
to view an advertisement more favorably and purchase the advertised
product or service. Systems described herein can be used to
identify, select, and present product, service, program,
advertisement, or other information to a user without user
intervention based on predicted compatibility with user biometrics
and demographics.
[0120] Non-limiting examples of user biometrics are shown in FIG.
13. User biometrics factors include user information, such as
emotional state, community interactions, hobbies, interests,
occupation, environmental influences, health biometrics, diet,
fitness level, exercise habits, and medical intervention. Emotional
state describes the psychological or mental state of the user,
which can fluctuate based on the physiological health of the user.
Emotional states can affect user compliance to health
recommendations, which can contribute to poor disease prognosis.
Community interactions and hobbies can describe user interests and
social network, which can provide information on user lifestyle
preferences. User occupation can provide information about user
fitness level and occupational therapy. Systems disclosed herein
can process user occupational or daily activity information to
generate personalized and integrated health recommendations.
Environmental influences can include weather, climate, and
elevation based on the location of the user. Health biometrics can
include cardiovascular biometrics, blood glucose level, insulin
level, heart rate, pulse rate, pulse oximetry, body fat percentage,
visceral fat percentage, muscle mass percentage, respiration rate,
respiratory quotient, bone mass, body water, body mass index,
weight, internal body temperature, external temperature, cortisol
level, ketone level, hormone levels, and medication usage. Diet is
a major contributor to overall health of an individual. For
metabolic diseases, such as diabetes, diet and nutrition play a
crucial role in disease management. Monitoring and improving
dietary habits can improve disease prognosis. Fitness level and
exercise habits can provide information of the physical health of
an individual. Systems disclosed herein can provide instructional
exercises that match an individual's fitness level and exercise
preferences, which can improve exercise adherence and prevent the
likelihood of injury. Medical interventions or medications used by
an individual can provide information about health state, disease
prognosis, and potential side effects that can influence the type
of health guidance provided by a system described herein.
[0121] FIG. 14 illustrates a computer system 1400 programmed or
otherwise configured to allow monitoring of a biometric of a
subject by biometric sensors 1406 or external biometric devices
1410, presentation of an instructional exercise by instructional
exercise module 1408, and presentation of an advertisement by
advertisement module 1409, in accordance with various embodiments
of the disclosure. The computer system 1400 includes a server 1402,
a CPU 1403, a memory 1404, a storage unit 1405, biometric sensors
1406, and a communication interface 1407.
[0122] The system 1400 receives a biometric measurement of a
subject from biometric sensors 1406 or external devices 1410, for
example, a biometric device. The system 1400 then generates by
instructional exercise module 1408 an instructional exercise for
the subject to perform based on the detected or received biometric
measurement. The system 1400 generates an advertisement by
advertisement module 1409 that is targeted to a subject based on a
subject's real-time biometrics, which can be stored in storage unit
1405 or received from external devices 1410. Communication
interface 1407 presents the instructional exercise and
advertisement multimedia generated from the subject's real-time
biometrics.
[0123] In some embodiments, the system 1400 generates a targeted
advertisement while a subject is performing the instructional
exercise provided by instructional exercise module 1408. In some
embodiments, the system 1400 generates a targeted advertisement
based on a historical biometric measurement in the subject detected
and/or received by the system.
[0124] Storage unit 1405 includes a database of instructional
exercises, which can be divided by various categories based on, for
example, type of exercise and the challenge level. Storage unit
1405 further includes a database of advertisements. In some
embodiments, instructional exercise and advertisement multimedia
can be provided via external devices.
[0125] FIG. 15 illustrates a system 1500 for biometrics-based
instructional exercise and advertising. The system for exercise
instruction 1500 includes a multimedia video content featuring
exercise instruction integrating content with software and devices
that track biometric data related to diabetes and/or health metrics
in real-time. The system 1500 combines presentation of
instructional exercise with the presentation of diabetes metrics
1501 integrating real-time biometric data, including active heart
rate of a user 1502, suggested glycogen depletion rate 1503, blood
glucose level 1504, graphic of instructional exercise 1505, name of
exercise 1506, and biometrics-based advertisement 1507.
[0126] Systems disclosed herein can present to a user demographic
group types of advertisements that match detected or predicted
interests and/or biometrics. Advertisements for products, services,
programs, and other information can be presented to a user through
various digital communications channels, including for example, a
mobile application, an e-mail, a text message, a social media
account, or any other communication medium that provides access
points to a user.
[0127] Further, systems disclosed herein can engage with users
through multimedia communication systems to improve the quality of
targeted advertising based on personal preferences of an individual
user. Increasing the ability of the user to control which
advertisements are received further improves user favorability of
targeted advertisements and increase likelihood that the user
purchases the advertised product or service. For example, a user
can be presented with questionnaires to gauge the user's interest
in a particular advertisement. User feedback can be integrated into
the biometric data analysis to refine the targeted advertising
process.
[0128] The targeted advertising systems disclosed herein can be
integrated with systems of exercise guidance based upon user
biometrics detected in real-time. Presentation of an advertisement
can be based on the type of exercise recommended by the system to
or selected by the user. For example, a user recommended to do
jogging exercises can be presented an advertisement for a social
running club or running accessory products. Presentation of an
advertisement can be based on changes in user biometrics during
performance of an exercise. For example, a user of the exercise
media device can be approaching completion of an exercise routine,
and the user's blood glucose level is detected to be low. The low
level necessitates that the user restores blood glucose levels by
food consumption. In response, the system can present to the user
advertisements for a food or beverage product suitable to adjust
the blood glucose level as needed.
[0129] Presentation of targeted advertising can also be based upon
an exercise recommendation provided by an instructional exercise
program. For example, a user performing or instructed to perform
weight lifting or resistance training exercises may be interested
in exercise accessory products. In response, the system can present
to the user advertisements for an exercise accessory product, for
example, weights, dumbbells, mats, exercise bands, or protective
gear.
[0130] Further, the targeted advertising systems disclosed herein
can present targeted advertising based on monitoring of user
interactions with multimedia. Monitoring user interactions with
multimedia enables the system to detect a user interest. User
identity profiles can be used to identify user market preferences.
The system can shape a user identity profile from information
obtained from monitoring of user interactions with multimedia. User
market preferences based on history of purchases can reflect the
future user purchasing interest. A user identity profile can be
determined in real-time. For example, a user who enjoys hiking can
have a user identity profile listing hiking as a user market
preference.
[0131] Non-limiting examples of ways in which the system can
monitor user multimedia interaction include clicks, browsing
history, purchase history, social media use history, calendars,
e-mail, message logs, call logs, and computing cookies. A user's
online presence in social media and non-social media websites can
be used to identify product preferences. Non-limiting examples of
social media websites include Facebook.RTM., YouTube.RTM.,
Instagram.RTM., Twitter.RTM., Reddit.RTM., Pinterest.RTM.,
Tumblr.RTM., Flickr.RTM., Google+.RTM., Meetup.RTM., Qzone.RTM.,
Weibo.RTM., and LinkedIn.RTM.. The monitoring can take place, for
example, on a personal computer, television, mobile device, tablet,
or video game console.
[0132] Prior to monitoring of user interactions and/or biometrics
for target advertising, users can opt in or out of tracking and/or
analysis of multimedia interaction for this purpose. In some
embodiments, the monitoring can be activated upon user approval. In
some embodiments, the monitoring can be activated without user
approval. The output of the monitoring can reported to a central
hub in which a computer system processes the output to determine
the user market preferences on the user interactions with media
devices.
[0133] Non-limiting examples of media devices include personal
computers, mobile telecommunications devices, tablet devices,
televisions, and video game consoles. Non-limiting examples of
media experiences include web browsing, social media browsing,
listening to sounds, music, or audio clips, watching a video or
program, such as a television program, playing a game, composing an
e-mail, texting, messaging, conversing, online shopping, and
otherwise participating in a media entertainment experience. The
advertisement can be an advertisement electronic communication
medium including, for example, a video or photograph.
[0134] The targeted advertising systems disclosed herein can allow
users to design the advertising experience manually. For example, a
user can hide or reject a received advertisement or notification by
selecting an icon on the advertisement communication. The user can
specify reasons for hiding the received advertisement. Reasons can
include, for example, because the advertisement is spam, offensive
or inappropriate, uninteresting, repetitive, not relevant. Thus,
the system can combine automatically-generated, biometrics-based
advertising with manual input of user advertising preferences. In
this way, the system can learn new user preferences and improve the
advertising experience for the user over time.
[0135] Users can further tailor the advertising experience by
creation of a user profile and select specific areas of interests,
for example, hobbies, interests, and general areas of interest to
guide the targeted advertising. A user can choose preferred
exercise types (e.g. pilates and running) or advertisement types
(e.g. services or products).
[0136] The system can present to a user a virtual catalog of
various user markets that can be chosen by the user. Once a user
interest has been identified, a system of the invention can launch
a program, such as a module, window, or notification via the media
associated with the user. The user can choose to access or ignore
the program. The program can present information to the user based
on a previously-identified interest. The information can relate to
a user market associated with the interest previously detected by
the system. For example, a user detected to have a history of
diabetes product purchases can be presented with products or
services related to diabetes or diabetic health management.
[0137] The program can present the user with a series of options,
for example, selectable icons. The selectable icons chosen for
presentation to the user relate to the user's identified interest.
Each icon can represent a different aspect or niche of the user
market, which suggests a product or service, or class of products
or services chosen by the user. The user can select any of the
icons to learn more about the products or services, and gain
information about how to purchase items or services of the desired
category. Upon selection of an icon, the user can be presented with
a second, third, or further series of icons, each delving more
narrowly and specifically into a market of interest to assist the
user with finding products/services of interest. Selecting a
selectable icon can be performed, for example, by clicking a
clickable icon, dragging and dropping an icon, sliding a selectable
icon, or by voice recognition of an icon to a command. The user can
navigate the system by selecting one or a plurality of selectable
icons. Each successive query module can probe deeper into a user
market and provide options and information at higher levels of
specificity to provide the user the most beneficial and productive
product or service search experience. The query module can also
detect that a selectable icon has been selected.
[0138] The user can select an icon, whereupon a system of the
invention recognizes that an icon has been selected. The computer
system associates the selected icon, for example, with a market, a
user market, a submarket, or a niche market, and uses the
association to guide a search for advertising likely to appeal to
the user. The computer system searches a database of advertisements
to identify those associated with the icons selected by the user.
Ultimately, the search finds advertisements associated with the
user's interest.
[0139] Once the desired advertisements have been identified, the
advertisements can be presented to the user over multimedia
devices. The user can browse and make selections for determination
of future types of targeted advertising. In doing so, the user can
learn about products of potential interest and contemplate
purchase. The user can be presented with advertisements for desired
products, and advertisements for products that the user might not
have considered previously, but may consider based on the user's
selections and the interest detected by the system.
[0140] For example, users can select "medical devices" as an
interest and subsequently choose "continuous glucose monitor" as a
preferred subcategory within the category of medical devices.
Users, advertisers, merchants, and publishers can select on any
number of selectable icons that are associated with a user market
associated with the media entertainment experience.
[0141] The efficiency and quality of the process can be improved by
monitoring the same user's media experiences across multiple media
devices. Monitoring can take place across two, three, or more media
devices. Non-limiting examples of media devices include a personal
computer, television, telephone, mobile device, tablet, and a video
game console. In some embodiments, the media devices are in
communication with a common host, such as a hub, a network, an
internet, an intranet, a server, a domain, or a computer system. In
some embodiments, communication takes place via a communication
module. The system can function on smartphones, tablets, desktop
computers, laptop computers, and a plurality of mobile devices with
a plurality of different interfaces and operating systems. This
versatility allows a user to have access to the system of the
invention on a plurality of distinct devices.
[0142] In some embodiments, the invention is provided in the form
of a computer program product comprising a computer-readable medium
having computer-executable code encoded therein, the
computer-executable code adapted to be executed to implement a
method for targeting advertising to a media user. Non-limiting
examples of computer-readable media include hard disk, floppy disk,
magnetic tape, flash drive, USB, CD, DVD, and Blu-ray Disc.
Non-limiting examples of computer-executable code include bytecodes
and portable codes such as Java, Small Talk, JIT, Python, PHP, CSS,
HTML5, DHTML, Forth, LLVM, and C++.
[0143] The system can comprise a computer program product that is
constantly received by and presented to an end-user while being
delivered by a provider, for example, by streaming media, and live
streaming. A system of the invention can use a plurality of
different network protocols, for example, user-datagram-protocols
(UDP), real time-streaming-protocols (RTSP),
real-time-transport-protocols (RTP), the
real-time-transport-control-protocols (RTCP), adaptive bitrate
streaming, and transmission-control-protocols (TCP) to deliver
advertisement.
[0144] For example, a user can be watching a cooking show
associated with the food, beverage, and nutritional supplement
industry. A system of the invention can match the user interest in
food/cooking, and offer industry-relevant product information as an
advertisement on the television screen. A user can choose to ignore
the advertisement or request further product information. A user
can choose to save the product information for later review. A user
can choose to review and purchase the advertised product or
service. In the case of purchase, a user can review the cost, and
provide information for shipping and complete payment as
appropriate.
[0145] The system can archive the data browsing activities
performed on devices associated with the system of the invention.
The system can also archive the data on a centralized data source.
For example, if a customer selects one or more icons with
information on "glucose monitors," the system can archive the data
to create a library with the interests of that customer. The
archive can guide future product suggestions and provide more rapid
advertising delivery. The archive can store information related to
viewed icons, selected icons, and purchased items, which can be
used to establish user profiles over time.
[0146] Targeted advertising content can contain, for example,
product or service information, event information, purchase
information, sales information, virtual and in-store offers,
virtual and in-store events, information on loyalty programs,
educational information, religious information, travel information,
and a plurality of niche advertisement specified by the user. For
example, an advertising output module can guide a user to purchase
a product or service. An advertising module can inform a user of an
upcoming in-store sales event or promotional period.
[0147] In some embodiments, the system can connect with a third
party market channel, including third party web sites. Users can
receive targeted advertisement from the system of the invention
while navigating a third party market channel. The user can
effectuate purchases and subscriptions at a third party market
channel. In some embodiments, the user can effectuate purchases and
subscriptions through an interface of the system.
Clinical Trial Recruitment Based on Biometric Data
[0148] Patient candidate recruitment is a critical bottleneck in
the clinical trials process. Recruitment of adequate numbers of
patients ("cohorts") for clinical trials can be challenging. The
problem is even more severe for clinical studies of therapies used
for treatment of rare or complex diseases, and the diseases and
treatments that are influenced by multiple factors including, for
example, age, gender, ethnicity, comorbidities, behavioral issues,
and additional treatment programs, including the use of one or more
medications, devices, or therapeutic regimens. For these reasons,
clinical trial recruitment is often laborious, expensive, time
consuming, and inefficient. In addition, patients who are
interested in participating in clinical trials are seldom directly
informed about clinical trials that fit the specific demographics
and biometric profile of the patient. Targeted advertising of
clinical trials to eligible patients can lead to improved rates of
clinical trial recruitment.
[0149] Clinical trial recruitment systems disclosed herein can
obtain and compile biometric data from multiple users through
multimedia devices communicatively coupled to an external server.
Compiled biometric data can be analyzed to determine patient
eligibility for clinical trial studies. For example, patient
electronic health records and biometric data can be used to
determine clinical trial eligibility. Patient candidates must meet
certain static criteria and/or dynamic criteria to qualify for a
particular study. Static criteria can include, for example, disease
diagnosis, medical history, gender, age, sex, ethnicity, location,
body mass index (BMI), and genotype. Dynamic criteria can include,
for example, biometric fluctuations in real-time, fluctuations in
blood glucose levels over different lengths of time, fluctuations
in blood glucose levels based on different types of exercise,
fluctuations in blood glucose levels based on the time and dosing
of different types of medications, and fluctuations in blood
glucose levels based on food intake.
[0150] Clinical researchers, principal investigators, or other
clinical trial designers can specify patient eligibility
requirements that are used to identify patient biometrics that
match the eligibility requirements of a particular clinical trial.
A patient database can include users of an instruction exercise
program described herein.
[0151] The system can analyze compiled patient databases to
determine eligible patient participants for a particular clinical
trial study. After determining patient eligibility, the system can
present to eligible patients targeted multimedia notifications
about a relevant clinical trial and provide a connection to
eligible patients with clinicians or researchers for further
consultation. The system can also provide clinicians or researchers
with eligible patient information, for example, the number of
eligible patients, patient medical history and other health
biometrics, and patient contact information.
[0152] In some embodiments, the system can analyze compiled
clinical trial databases to determine available clinical trial
studies for a patient seeking to participate in a clinical trial.
Non-limiting examples of users of the systems described herein
include clinical researchers, principal investigators, physicians,
health care professionals, and patients.
[0153] The clinical trial recruitment system can begin with a
patient accessing an exercise guidance program on a media device.
The exercise guidance program can monitor and record user
biometrics in real-time. The recorded biometric data can be
transmitted to the clinical trial recruitment system for analysis.
Patient eligibility can change based on a change in a user
biometric. Non-limiting examples of media devices include personal
computers, mobile devices, televisions, and video game consoles.
Non-limiting examples of user biometrics include disease diagnosis,
medical conditions, electronic health records, medical history,
family medical history, patient medications, exercise history, risk
factors, age, sex, demographics, and other criteria relevant to
clinical trial eligibility.
[0154] Prior to analysis of user biometrics for identification of
clinical trial eligibility, users can opt in or out of tracking
and/or analysis of user biometrics for this purpose. Furthermore,
users can opt in or out of receiving notifications regarding open
clinical trials.
[0155] FIG. 16 illustrates a computer system 1600 programmed or
otherwise configured to allow monitoring of a biometric of a
subject by biometric sensors 1606 or external biometric devices
1610, presentation of an instructional exercise by instructional
exercise module 1608, and presentation of a clinical trial
notification by clinical trial module 1609, in accordance with
various embodiments of the disclosure. The computer system 1600
includes a server 1602, a CPU 1603, a memory 1604, a storage unit
1605, biometric sensors 1606, and a communication interface
1607.
[0156] The system 1600 receives a biometric measurement of a
subject from biometric sensors 1606 or from external devices 1614,
for example, a biometric device. The system 1600 then generates by
instructional exercise module 1608 an instructional exercise for
the subject to perform based on the detected or received biometric
measurement. The system 1600 further generates by clinical trial
module 1609 a notification about a clinical trial study that may be
relevant to the subject based on the subject's real-time
biometrics. Communication interface 1607 presents the instructional
exercise and advertisement multimedia generated from the subject's
real-time biometrics, which can be stored in storage unit 1405 or
received from external devices 1410. Communication interface 1607
can further provide a connection to the subject with a clinician or
researcher for further consultation.
[0157] In some embodiments, clinical trial module 1609 determines
eligibility of the subject for a particular clinical trial based on
subject biometrics received during performance of the instructional
exercise. In some embodiments, the system 1600 determines clinical
trial eligibility based on a historical biometric measurement in
the subject detected and/or received by the system.
[0158] Storage unit 1605 includes a database of instructional
exercises, which can be divided by various categories based on, for
example, type of exercise and the challenge level. Storage unit
1605 further includes a database of clinical trials and associated
patient eligibility filters, for example, disease type and
comorbidities. In some embodiments, instructional exercise and
clinical trial multimedia can be provided via external devices.
[0159] FIG. 17 illustrates a system 1700 for biometrics-based
instructional exercise and clinical trial recruitment. The system
for exercise instruction 1700 includes a multimedia video content
featuring exercise instruction integrating content with software
and devices that track biometric data related to diabetes and/or
health metrics in real-time. The system 1700 combines presentation
of instructional exercise with the presentation of diabetes metrics
1701 integrating real-time biometric data, graphic of instructional
exercise 1701, name of exercise 1702, calorie expenditure and
geospatial distance covered 1703, amount of time per exercise 1704,
and biometrics-based clinical trial notification 1705.
Biometrics Monitoring
[0160] Systems described herein can be configured to receive
biometric data from a broad array of multimedia devices, for
example, sensors, wearable devices, and/or medication delivery
devices (e.g., insulin pumps and glucagon pumps). Biometric data
can be collected from manual, periodic user input. Biometric data
can be collected from continuous, real-time data received from a
biometric sensing device with automated data interfaces. Manual and
automated data are unique to individual users. Biometric data can
be used to determine types of products, services, programs, or
information that may interest a user. Accordingly, systems
described herein can be used to identify, select, and present
product, service, program, advertisement, or other information to a
user without user intervention.
[0161] Biometric data can include, for example, cardiovascular
biometrics, blood glucose level, insulin level, heart rate, pulse
rate, pulse oximetry, body fat percentage, visceral fat percentage,
muscle mass percentage, respiration rate, respiratory quotient,
bone mass, body water, body mass index, weight, internal body
temperature, external temperature, cortisol level, catecholamine
level (e.g., epinephrine, norepinephrine, and dopamine), ketone
level, hormone level, and medication usage. In some embodiments,
biometric data can include sleeping habits, emotional states, and
psychological state.
Integration of Diabetes Exercise Algorithms into Closed-Loop
Systems
[0162] Disclosed herein are methods, kits, systems, and devices
incorporating algorithms for exercise guidance and instruction
specific to diabetes relief and management into closed-loop or
artificial pancreas systems. Such closed-loop systems include a
device configured to monitor glucose levels and a device configured
to deliver a compound to a subject. The loop begins with assessment
of glucose levels in the subject. This assessment, if measured to
be outside of a pre-determined range, is followed by transmission
of a notification by the glucose monitoring device to the compound
delivery device. This notification is followed by adjustment of the
rate of compound delivery based upon the measured glucose level.
The loop is closed by subsequent measurement of glucose levels by
the glucose monitoring device.
[0163] A glucose monitoring device can include continuous glucose
monitoring (CGM) devices or non-continuous glucose monitoring
devices, for example, blood glucose meters (BGM). A CGM device can
be a Bluetooth.RTM.-enabled device that electronically transmits
glucose monitoring data from a glucose sensing device to a
telecommunications device.
[0164] In some embodiments, the disclosure provides methods for
adjusting the interaction of the components of a closed-loop system
based upon an exercise recommendation. In some embodiments, the
rate of insulin delivery is decreased based upon the exercise
recommendation. In some embodiments, the rate of insulin delivery
is increased based upon the exercise recommendation. In some
embodiments, the rate of glucagon delivery is decreased based upon
the exercise recommendation. In some embodiments, the rate of
glucagon delivery is increased based upon the exercise
recommendation.
[0165] FIG. 3 illustrates an embodiment of a closed-loop system 300
of the disclosure. The closed-loop system 300 comprises a
continuous glucose monitor 301. When the continuous glucose monitor
301 measures a glucose value outside of a pre-determined range, the
continuous glucose monitor 301 transmits a notification 302 to an
insulin pump 303. The insulin pump 303 incorporates information
relating to the exercise algorithms disclosed herein to adjust the
insulin rate to return the glucose value to within an acceptable
range based upon the calculated impact of the exercise activity on
the glucose value. For example, if an exercise activity that would
lower the blood glucose level, such as moderately paced hiking, was
suggested by the algorithm, the closed-loop system 300 would
account for this exercise activity to deliver a reduced rate of
insulin to the subject.
[0166] FIG. 4 illustrates an embodiment of a closed-loop system 400
of the disclosure. The closed-loop system 400 comprises a
continuous glucose monitor 401. When the continuous glucose monitor
401 measures a glucose value outside of a pre-determined range, the
continuous glucose monitor 401 transmits a notification 402 to a
telecommunications device with a processor, such as a
telecommunications device 403. The telecommunications device 403
receives the notification 402 and incorporates the exercise
algorithms disclosed herein to provide an instruction 404 to a dual
insulin/glucagon pump 405. The dual insulin/glucagon pump 405
alters the rate of insulin and glucagon delivery to return the
glucose value to within an acceptable range based upon the
calculated impact of the exercise activity on the glucose
value.
[0167] A heart rate monitor 406 is also in communication with
telecommunications device 403. The heart rate monitor 406 can
detect the subject's heart rate prior to, during, and after
exercise, and communicate 407 the heart rate to telecommunications
device 403. The heart rate that is communicated to
telecommunications device 403 can influence the determination of
other important factors, including the type of exercise instruction
given to the subject, the dose of insulin to administer, the dose
of glucagon to administer, whether to warn the subject of an unsafe
circumstance, whether to advise the subject to consume a source of
carbohydrates, or whether to terminate exercise. An external camera
408 record the subject's motions during exercise to provide a
real-time camera feed. External cameras can be used to capture the
user's image for video production, broadcast, image analysis, or
uni-directional and bi-directional communication. Image analysis
can refer to the analysis of user images captured by cameras using
automated assessment tools, screened and interpreted using human
experts and/or artificial intelligence to identify a broad range of
physiological, behavioral, or environmental patterns. Non-limiting
examples of image patterns include changes in the user's facial
complexion, body posture, facial expression, respiration,
perspiration, body temperature, and performance of correct or
incorrect movements.
[0168] For example, if an exercise activity that would raise the
blood glucose level or alter heart rate, such as heavy
weightlifting, was suggested by the algorithm, the closed-loop
system 400 would account for this exercise activity to deliver an
increased rate of insulin and decreased rate of glucagon to the
subject.
[0169] In some embodiments, devices utilizing algorithms of the
disclosure communicate instructions to, or receive instructions
from, other devices as a component of a kit or system of the
disclosure. All communications can be performed as disclosed
herein, in the reverse, or in both directions.
[0170] In some embodiments, a glucose monitoring device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucose monitoring device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucagon delivery
device to administer glucagon.
[0171] In some embodiments, a glucose monitoring device, utilizing
an algorithm of the disclosure, communicates an instruction to a
telecommunications device, which communicates the instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucose monitoring device, utilizing an algorithm of the
disclosure, communicates an instruction to a telecommunications
device, which communicates the instruction to a glucagon delivery
device to administer glucagon. In some embodiments, a glucose
monitoring device, utilizing an algorithm of the disclosure,
communicates an instruction to a telecommunications device, which
communicates the instruction to an insulin delivery device, which
communicates the instruction to a glucagon delivery device to
administer glucagon. In some embodiments, a glucose monitoring
device, utilizing an algorithm of the disclosure, communicates an
instruction to a telecommunications device, which communicates the
instruction to a glucagon delivery device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0172] In some embodiments, a glucose monitoring device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device, which communicates the instruction to a
glucagon delivery device to administer glucagon. In some
embodiments, a glucose monitoring device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucagon delivery
device, which communicates the instruction to an insulin delivery
device to administer insulin. In some embodiments, a glucose
monitoring device, utilizing an algorithm of the disclosure,
communicates an instruction to an insulin delivery device, which
communicates the instruction to a telecommunications device, which
communicates the instruction to a glucagon delivery device to
administer glucagon. In some embodiments, a glucose monitoring
device, utilizing an algorithm of the disclosure, communicates an
instruction to a glucagon delivery device, which communicates the
instruction to a telecommunications device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0173] In some embodiments, a telecommunications device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device to administer insulin. In some embodiments,
a telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucagon delivery
device to administer glucagon. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to an insulin delivery
device to administer insulin. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to a glucagon delivery
device to administer glucagon.
[0174] In some embodiments, a telecommunications device, utilizing
an algorithm of the disclosure, communicates an instruction to a
glucose monitoring device, which communicates the instruction to an
insulin delivery device, which communicates the instruction to a
glucagon delivery device to administer glucagon. In some
embodiments, a telecommunications device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to a glucagon delivery
device, which communicates the instruction to an insulin delivery
device to administer insulin. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to an insulin delivery
device, which communicates the instruction to a glucose monitoring
device, which communicates the instruction to a glucagon delivery
device to administer glucagon. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucagon delivery
device, which communicates the instruction to a glucose monitoring
device, which communicates the instruction to an insulin delivery
device to administer insulin.
[0175] In some embodiments, a telecommunications device, utilizing
an algorithm of the disclosure, communicates an instruction to a
glucagon delivery device, which communicates the instruction to a
glucose monitoring device to measure a glucose level. In some
embodiments, a telecommunications device, utilizing an algorithm of
the disclosure, communicates an instruction to an insulin delivery
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucagon delivery
device, which communicates the instruction to an insulin delivery
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, a
telecommunications device, utilizing an algorithm of the
disclosure, communicates an instruction to an insulin delivery
device, which communicates the instruction to a glucagon delivery
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level.
[0176] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucagon delivery device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucose monitoring
device to measure a glucose level.
[0177] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to a
telecommunications device, which communicates the instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucagon delivery device, utilizing an algorithm of the
disclosure, communicates an instruction to a telecommunications
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, a glucagon
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to a telecommunications device, which
communicates the instruction to an insulin delivery device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, a glucagon delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a telecommunications device, which communicates the
instruction to a glucose monitoring device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0178] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device, which communicates the instruction to a
glucose monitoring device to measure a glucose level. In some
embodiments, a glucagon delivery device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to an insulin delivery
device to administer insulin. In some embodiments, a glucagon
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to an insulin delivery device, which
communicates the instruction to a telecommunications device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, a glucagon delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a glucose monitoring device, which communicates the
instruction to a telecommunications device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0179] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucagon delivery device, utilizing an algorithm of the
disclosure, communicates an instruction to a glucose monitoring
device to measure a glucose level.
[0180] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to a
telecommunications device, which communicates the instruction to an
insulin delivery device to administer insulin. In some embodiments,
a glucagon delivery device, utilizing an algorithm of the
disclosure, communicates an instruction to a telecommunications
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, a glucagon
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to a telecommunications device, which
communicates the instruction to an insulin delivery device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, a glucagon delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a telecommunications device, which communicates the
instruction to a glucose monitoring device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0181] In some embodiments, a glucagon delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to an
insulin delivery device, which communicates the instruction to a
glucose monitoring device to measure a glucose level. In some
embodiments, a glucagon delivery device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to an insulin delivery
device to administer insulin. In some embodiments, a glucagon
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to an insulin delivery device, which
communicates the instruction to a telecommunications device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, a glucagon delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a glucose monitoring device, which communicates the
instruction to a telecommunications device, which communicates the
instruction to an insulin delivery device to administer
insulin.
[0182] In some embodiments, an insulin delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to a
glucagon delivery device to administer glucagon. In some
embodiments, an insulin delivery device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucose monitoring
device to measure a glucose level.
[0183] In some embodiments, an insulin delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to a
telecommunications device, which communicates the instruction to a
glucagon delivery device to administer glucagon. In some
embodiments, an insulin delivery device, utilizing an algorithm of
the disclosure, communicates an instruction to a telecommunications
device, which communicates the instruction to a glucose monitoring
device to measure a glucose level. In some embodiments, an insulin
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to a telecommunications device, which
communicates the instruction to a glucagon delivery device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, an insulin delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a telecommunications device, which communicates the
instruction to a glucose monitoring device, which communicates the
instruction to a glucagon delivery device to administer
glucagon.
[0184] In some embodiments, an insulin delivery device, utilizing
an algorithm of the disclosure, communicates an instruction to a
glucagon delivery device, which communicates the instruction to a
glucose monitoring device to measure a glucose level. In some
embodiments, an insulin delivery device, utilizing an algorithm of
the disclosure, communicates an instruction to a glucose monitoring
device, which communicates the instruction to a glucagon delivery
device to administer glucagon. In some embodiments, an insulin
delivery device, utilizing an algorithm of the disclosure,
communicates an instruction to a glucagon delivery device, which
communicates the instruction to a telecommunications device, which
communicates the instruction to a glucose monitoring device to
measure a glucose level. In some embodiments, an insulin delivery
device, utilizing an algorithm of the disclosure, communicates an
instruction to a glucose monitoring device, which communicates the
instruction to a telecommunications device, which communicates the
instruction to a glucagon delivery device to administer
glucagon.
[0185] FIG. 5 depicts communications among components of a
closed-loop system 500. The closed-loop system 500 includes a
telecommunications device 501, a glucose monitoring device 502, an
insulin delivery device 503, and a glucagon delivery device 504.
The glucose monitoring device 502, utilizing an algorithm of the
disclosure, can transmit an instruction 505 to the insulin delivery
device 503, and the insulin delivery device 503, utilizing an
algorithm of the disclosure, can transmit an instruction 506 to the
glucose monitoring device 502. The glucose monitoring device 502
can transmit an instruction 507, utilizing an algorithm of the
disclosure, to the telecommunications device 501, and the
telecommunications device 501, utilizing an algorithm of the
disclosure, can transmit an instruction 508 to the glucose
monitoring device 502. The glucose monitoring device 502 can
transmit an instruction 509, utilizing an algorithm of the
disclosure, to the glucagon delivery device 504, and the glucagon
delivery device 504, utilizing an algorithm of the disclosure, can
transmit an instruction 510 to the glucose monitoring device 502.
The telecommunications device 501, utilizing an algorithm of the
disclosure, can transmit an instruction 511 to the insulin delivery
device 503, and the insulin delivery device 503, utilizing an
algorithm of the disclosure, can transmit an instruction 512 to the
telecommunications device 501. The telecommunications device 501
can transmit an instruction 513, utilizing an algorithm of the
disclosure, to the glucagon delivery device 504, and the glucagon
delivery device 504, utilizing an algorithm of the disclosure, can
transmit an instruction 514 to the telecommunications device 501.
The insulin delivery device 503 can transmit an instruction 515,
utilizing an algorithm of the disclosure, to the glucagon delivery
device 504, and the glucagon delivery device 504, utilizing an
algorithm of the disclosure, can transmit an instruction 516 to the
insulin delivery device 503. Any or all of the components of the
system can be present in a single housing. Any or all of the
components, or the single housing can be implantable or implanted
in the subject.
[0186] FIG. 5 further depicts a heart rate monitor 517, connected
to the other components by dashed lines. The heart rate monitor
517, utilizing an algorithm of the disclosure, can transmit an
instruction 522 to the insulin delivery device 503, and the insulin
delivery device 503, utilizing an algorithm of the disclosure, can
transmit an instruction 523 to the heart rate monitor 517. The
heart rate monitor 517 can transmit an instruction 520, utilizing
an algorithm of the disclosure, to the telecommunications device
501, and the telecommunications device 501, utilizing an algorithm
of the disclosure, can transmit an instruction 521 to the heart
rate monitor 517. The heart rate monitor 517 can transmit an
instruction 523, utilizing an algorithm of the disclosure, to the
glucagon delivery device 504, and the glucagon delivery device 504,
utilizing an algorithm of the disclosure, can transmit an
instruction 522 to the heart rate monitor 517. The heart rate
monitor 517 can transmit an instruction 518, utilizing an algorithm
of the disclosure, to the glucose monitoring device 502, and the
glucose monitoring device 502, utilizing an algorithm of the
disclosure, can transmit an instruction 519 to the heart rate
monitor 517. Any or all of the components of the system can be
present in a single housing. Any or all of the components, or the
single housing can be implantable or implanted in the subject.
Computer Processing for Diabetes Exercise Algorithms
[0187] FIG. 6 shows a computer system 600 programmed or otherwise
configured to allow a subject to monitor a glucose level and
transmit a reading of the glucose level; to instruct administration
of hormone to the subject; to instruct a state of physical exercise
through an exercise instructional video; to display a reading of a
biometric data of the subject; or to instruct an exercise
instructional video to stop and to present an alternative exercise
instructional video, in accordance with various embodiments of the
present disclosure. The system 600 includes a computer server
("server") 601 that is programmed to implement methods disclosed
herein. The server 601 includes a central processing unit 602,
which can be a single core or multi core processor, or a plurality
of processors for parallel processing. The server 601 also
includes: memory 603, such as random-access memory, read-only
memory, and flash memory; electronic storage unit 604, such as a
hard disk; communication interface 605, such as a network adapter,
for communicating with one or more other systems; and peripheral
devices 606, such as cache, other memory, data storage, and
electronic display adapters. The memory 603, storage unit 604,
interface 605 and peripheral devices 606 are in communication with
the CPU 602 through a communication bus, such as a motherboard. The
storage unit 604 can be a data storage unit or data repository for
storing data. The server 601 can be operatively coupled to a
computer network (hereinafter "network") 607 with the aid of the
communication interface 605. The network 607 can be the Internet,
an internet or extranet, or an intranet or extranet that is in
communication with the Internet. The network 607 in some cases is a
telecommunications network or data network. The network 607 can
include one or more computer servers, which can allow distributed
computing, such as cloud computing. The network 607, in some cases
with the aid of the server 601, can implement a peer-to-peer
network, which can allow devices coupled to the server 601 to
behave as a client or an independent server.
[0188] The storage unit 604 can store files, such as files related
to biometric data, glucose level readings, basal and adjusted rates
of hormone administration, body weight, time of day of physical
exercise, type of physical exercise, and duration of physical
exercise. The storage unit 604 can store media items, such as
exercise instruction videos of the disclosure. The storage unit 604
can store subject data, such as biometric data, glucose level
readings, basal and adjusted rates of hormone administration, body
weight, time of day of physical exercise, type of physical
exercise, and duration of physical exercise at various points in
time. The server 601 in some cases can include one or more
additional data storage units that are external to the server 601,
such as located on a remote server that is in communication with
the server 601 through an intranet or the Internet. The storage
unit 604 can store videos that provide exercise instruction, as
well as items included in videos that provide exercise instruction,
such as real-time biometric data collected during the performance
of physical exercise with the video.
[0189] The server 601 can communicate with one or more remote
computer systems through the network 607. In some embodiments, the
server 601 is in communication with a first computer system 608 and
a second computer system 609 that are located remotely with respect
to the server 501. The first computer system 608 can be the
computer system of a first subject, and the second computer system
609 can be that of a second subject, such as a personal trainer or
third-party healthcare provider, such as a doctor, a nurse, or a
dietician. The first computer system 608 and second computer system
609 can be, for example, personal computers, such as a portable PC;
slate and tablet PC, such as Apple.RTM. iPad and Samsung.RTM.
Galaxy Tab; telephones; smartphones, such as Apple.RTM. iPhone,
Android-enabled device, Google.RTM. Pixel, Windows.RTM. Phone, and
Blackberry.RTM.; smart watches, such as Apple.RTM. Watch; smart
glasses, such as Google.RTM. Glass; or personal digital assistants.
The first or second subject can access the server 601 via the
network 607 to view or manage an exercise instruction video.
[0190] In some situations, the system 600 includes a single server
601. In other situations, the system 600 includes multiple servers
in communication with one another through an intranet or the
Internet. The server 601 can be adapted to store subject profile
information, such as, for example, a name, physical address, email
address, telephone number, instant messaging (IM) handle,
educational information, work information, social likes or dislikes
and historical information, such as information that can relate to
the progress of a subject in exercise instruction, and other
information of potential relevance to the subject. Such profile
information can be stored on the storage unit 604 of the server
601.
[0191] Methods as described herein can be implemented by way of a
machine- or computer-executable code or software stored on an
electronic storage location of the server 601, such as, for
example, on the memory 603 or electronic storage unit 604. During
use, the code can be executed by the processor 602. In some cases,
the code can be retrieved from the storage unit 604 and stored on
the memory 603 for ready access by the processor 602, for example,
computer-executable code for hormone administration while a subject
is in a state of physical rest prior to the subject being in a
state of physical exercise. In some situations, the electronic
storage unit 604 can be precluded, and machine-executable
instructions are stored on memory 603. Alternatively, the code can
be executed on the second computer system 609. The code can be
pre-compiled and configured for use with a processor adapted to
execute the code, or can be compiled during runtime. The code can
be supplied in a programming language that can be selected to allow
the code to execute in a precompiled or as-compiled fashion.
[0192] All or portions of the software can at times be communicated
through the Internet or various other telecommunications networks.
Such communications can support loading of the software from one
computer or processor into another, for example, from a management
server or host computer into the computer platform of an
application server. Another type of media that can bear the
software elements includes optical, electrical and electromagnetic
waves, such as those used across physical interfaces between local
devices, through wired and optical landline networks and over
various air-links. The physical elements that carry such waves,
such as wired or wireless links, or optical links, also can be
considered as media bearing the software.
[0193] A machine-readable medium, incorporating computer-executable
code, can take many forms, including a tangible storage medium, a
carrier wave medium, and physical transmission medium. Non-limiting
examples of non-volatile storage media include optical disks and
magnetic disks, such as any of the storage devices in any computer,
such as can be used to implement the databases of FIG. 6. Volatile
storage media include dynamic memory, such as a main memory of such
a computer platform. Tangible transmission media include coaxial
cables, copper wire and fiber optics, including wires that comprise
a bus within a computer system. Carrier-wave transmission media can
take the form of electric or electromagnetic signals, or acoustic
or light waves such as those generated during radio frequency (RF)
and infrared (IR) data communications.
[0194] Common forms of computer-readable media include: a floppy
disk, a flexible disk, hard disk, magnetic tape, any other magnetic
medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch
cards paper tape, any other physical storage medium with patterns
of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other
memory chip or cartridge, a carrier wave transporting data or
instructions, cables or links transporting such a carrier wave, and
any other medium from which a computer can read programming code or
data. Many of these forms of computer readable media can be
involved in carrying one or more sequences of one or more
instructions to a processor for execution.
[0195] The server 601 can be configured for: data mining; extract,
transform and load (ETL); or spidering operations, including Web
Spidering where the system retrieves data from remote systems over
a network and access an Application Programming Interface or parses
the resulting markup, which can permit the system to load
information from a raw data source or mined data into a data
warehouse. The data warehouse can be configured for use with a
business intelligence system, such as Microstrategy.RTM. and
Business Objects.RTM.. The system can include a data mining module
adapted to search for media items in various source locations, such
as email accounts and various network sources, such as social
networking accounts, such as Facebook.RTM., Foursquare.RTM.,
Google+.RTM., and LinkedIn.RTM., or on publisher sites, such as
weblogs.
[0196] An exercise instruction video can be presented to a subject
on a subject interface (UI) of an electronic device of the subject.
Non-limiting examples of UIs include a graphical subject interface
(GUI) and web-based subject interface. A GUI can allow a subject to
access an exercise instruction video. The GUI can allow a subject
to edit the exercise instruction video, such as upload items to the
exercise instruction video to display to other subjects in a manner
selected by the subject. The UI, such as GUI, can be provided on a
display of an electronic device of the subject. The display can be
a capacitive or resistive touch display, or a head-mountable
display, such as a Google.RTM. Glass. Such displays can be used
with other systems and methods of the disclosure.
[0197] Methods of the disclosure can be facilitated with the aid of
applications, or apps, that can be installed on an electronic
device of the subject. An app can include a GUI on a display of the
electronic device of the subject. The app can be programmed or
otherwise configured to perform various functions of the system,
such as, for example, permitting a subject to manage, such as
create and edit, an exercise instructional program. GUIs of apps
can display on an electronic device of the subject. Non-limiting
examples of electronic devices include computers, televisions,
smartphones, tablets, and smart watches. The electronic device can
include, for example, a passive screen, a capacitive touch screen,
or a resistive touch screen. The electronic device can include a
network interface and a browser that allows the subject to access
various sites or locations, such as web sites, on an intranet or
the Internet. The app is configured to allow the mobile device to
communicate with a server, such as the server 601.
Diabetes Exercise Algorithm Integration into External Devices
[0198] Methods, systems, kits, and devices of the disclosure can
incorporate diabetes exercise algorithms into external devices.
Non-limiting examples of external devices that can incorporate
diabetes exercise algorithms include external insulin delivery
devices, external glucagon delivery devices, and external glucose
monitoring devices.
[0199] In some embodiments, the subject receives or is administered
the dose of hormone through an external hormone delivery device in
contact with the subject. In some embodiments, the external hormone
delivery device is configured to pump hormone. In some embodiments,
the external hormone delivery device is configured to inject
hormone. In some embodiments, the external insulin delivery device
and external glucagon delivery device are contained within a common
housing.
[0200] In some embodiments, a hormone pump is capable of automatic
injection a fixed amount of hormone at defined rates or time points
by driving a piston in a state where an injection needle is
inserted into a body fat region of the abdomen of the subject. In
the pump, an injector is mounted on a side of a box-type housing in
a longitudinal direction, and a push member is mounted at a lower
section of the injector to drive the injector. The injector
includes a cylindrical syringe for containing hormone therein and a
piston inserted into the syringe for pushing the hormone through a
tube. A disk-type push member is mounted on the lower end of the
piston, and a female screw is formed at the center of the push
member.
[0201] A motor and a power supply, which has a number of
deceleration gear lines for decelerating a rotational speed of the
motor, are mounted on the lower portion of the box-type housing,
and a rotary shaft is mounted on a final gear of the deceleration
gear lines. The rotary shaft has a male screw of the
circumferential surface thereof, and the male screw is coupled with
the female screw of the push member. As a result, the push member
advances according to the rotation of the rotary shaft, the piston
advances inside the syringe, and thereby, the hormone corresponding
to an advanced amount of the piston is injected into the subject
through the tube and an injection needle. In some embodiments, the
hormone pump includes a cover to allow the injector to be drawn to
the outside of the box-type housing when the hormone is loaded into
the pump. In some embodiments, the hormone pump includes a
connector for connecting the tube to the syringe. In some
embodiments, the hormone pump includes a sealing cap for preventing
penetration of moisture into the power supply.
[0202] In some embodiments, the subject measures a glucose level of
the subject through an external glucose monitoring device in
contact with the subject. In some embodiments, the external glucose
monitoring device is a glucose meter device. In some embodiments,
the external glucose monitoring device is a continuous glucose
monitoring device. In some embodiments, the continuous glucose
monitoring device is implanted underneath the skin.
[0203] Two major classes of glucose monitoring devices are used by
subjects: (1) non-continuous or single-point glucose monitoring
devices, such as blood glucose meters and blood glucose test
strips; and (2) continuous glucose monitoring devices.
Non-continuous glucose monitoring devices consist of meters and
test strips that require blood samples to be drawn from fingertips,
forearms, or legs. These glucose monitoring devices rely on lancing
and manipulation of the blood draw site.
[0204] Continuous glucose monitoring devices are implanted, for
example, subcutaneously, and measure glucose levels in the
interstitial fluid at various time points throughout the day, to
show trends in glucose levels over a period of time. As these
devices are implanted, use of a continuous glucose monitoring
devices requires the assistance of a health care professional.
Continuous glucose monitoring devices also require frequent, for
example, daily calibration using blood glucose results obtained
from non-continuous glucose monitoring devices. This repeated
calibration is helpful for maintaining sensor accuracy and
sensitivity.
[0205] In some embodiments, a continuous glucose monitoring device
has an array of hollow microneedles or other tissue piercing
elements extending through the stratum corneum of a subject into
the interstitial fluid beneath the stratum corneum. The
microneedles in the array are hollow and have open distal ends, and
their interiors communicate with a sensing area within a sensor
channel. The sensing area is therefore in fluid communication with
interstitial fluid through the microneedle array. The sensing area
and the microneedle array are pre-filled with sensing fluid prior
to the first use of the device. Thus, when the device is implanted
into the skin of the subject and the microneedles pierce the
stratum corneum of the skin, substantially no net fluid transfers
from the interstitial fluid into the microneedles, but instead
glucose diffuses from the interstitial fluid into the sensing fluid
within the needles.
[0206] Disposed above and in fluid communication with sensor
channel is a glucose sensor. In some embodiments, the glucose
sensor is an electrochemical glucose sensor that generates an
electrical signal, such as current, voltage and charge, whose value
depends on the concentration of glucose in the fluid within the
sensing area. A sensor electronics element receives the voltage
signal from the glucose sensor. In some embodiments, the sensor
electronics element uses the sensed signal to compute a glucose
concentration and display it. In other embodiments, sensor
electronics element transmits the sensed signal, or information
derived from the sensed signal, to a remote device, such as through
wireless communication. The continuous glucose monitoring device is
held in place on the skin by one or more adhesive pads.
[0207] In some embodiments, the continuous glucose monitoring
device has a built-in sensor calibration system. A reservoir
comprises a sensing fluid with, for example, a glucose
concentration from about 1 mg/dL to about 400 mg/dL. In some
embodiments, the glucose concentration in the sensing fluid is
selected to be below the glucose sensing range of the sensor. The
sensing fluid can comprise buffers, preservatives, or other
substances in addition to glucose. Upon actuation of a manual or
automatic pump, plunger or other actuator, sensing fluid is forced
from the reservoir through a first check valve, such as a flap
valve, into a sensing channel. The sensing fluid within the sensing
channel is forced through a second check valve, such as a flap
valve, into a waste reservoir. Check valves or similar gating
systems are used to reduce the likelihood of contamination. Because
the fresh sensing fluid has a known glucose concentration, the
sensor is calibrated at this value to set a baseline. After
calibration, the sensing fluid in the sensing channel remains
stationary, and glucose from the interstitial fluid diffuses
through microneedles into the sensing area. Changes in the glucose
concentration over time reflect differences between the calibration
glucose concentration of the sensing fluid in the reservoir and the
glucose concentration of the interstitial fluid, which can be
correlated with the actual blood glucose concentration of the
subject. Because of possible degradation of the sensor or loss of
sensor sensitivity over time, the continuous glucose monitoring
device can be periodically recalibrated by manual or automatic
operation of the actuator to send fresh sensing fluid from the
reservoir into the sensing area.
[0208] In some embodiments, the glucose monitoring device can
measure other analytes, such as electrolytes, for example, sodium,
calcium, magnesium, zinc, iron, and potassium. In some embodiments,
the glucose monitoring device can use any suitable sensor
including, for example, an electrochemical sensor and an optical
sensor.
Virtual Health Assistant
[0209] Integrated analysis of user biometrics can be used to
promote positive lifestyle changes for effective, long-term health
management. Systems and methods disclosed herein can be integrated
with a virtual health assistant powered by artificial intelligence
and machine learning. Similar to digital trainers disclosed herein,
virtual assistants can receive and process user biometric data to
provide personalized health guidance and feedback in real-time. A
virtual health assistant can receive and analyze user biometric
data using artificial intelligence platforms including, for
example, machine learning, natural language processing, and speech
recognition.
[0210] A virtual health assistant can provide step-by-step
guidance, for example, for a newly diagnosed diabetes patient who
can benefit from individualized guidance with adapting to new
lifestyle changes. A virtual health assistant can provide
notifications or reminders to complete diabetes management tasks
based on a user's personalized routine in real-time. Health
management tasks can include, for example, completing an exercise
routine, administering a medication, administering insulin,
administering glycogen, monitoring blood glucose level, monitoring
blood pressure, and consuming a food or beverage.
[0211] A virtual health assistant can provide 24/7, round-the-clock
access to a lifestyle coach to enhance health management. The
virtual assistant can track user progress and maintain a
personalized daily schedule of health management tasks. The virtual
assistant can provide continuous virtual health check-ups, for
example, by monitoring user biometrics in real-time. Progress
tracking can include logging compliance with a scheduled regimen by
time-stamping and date-stamping completion of a task by a user in
real-time. Progress tracking can further include information about
adequacy of user performance of an exercise, for example, based on
user comfort and challenge level before, after, and during an
exercise regimen. User performance can be determined by real-time
biometrics. For example, real-time detection of heart rate and
pulmonary metrics during user performance of an exercise can be
determining factors of exercise performance, as well as the fitness
level of the user. Progress tracking can further include
recordation of user biometrics before, after, and during an
exercise regimen. User biometric information can be processed in
real-time to provide continuous improvements to the user's
personalized health regimen.
[0212] In some embodiments, the virtual health assistant can offer
provide lifestyle recommendations to improve the progress of the
user on a daily, weekly, monthly, or yearly basis. The virtual
assistant can recommend lifestyle recommendations in real-time
based on changes in user biometrics over time. Lifestyle
recommendations can include, for example, modifying sleeping
habits, exercise habits, diet, medication dosage, and social media
habits.
[0213] The system can also provide a communication medium between
the user and a healthcare provider. For example, when a user
biometrics is detected to be at a dangerous range, the system can
notify a healthcare provider.
[0214] In some embodiments, the virtual health systems described
herein can be integrated with other virtual assistant systems, for
example, Amazon.RTM. Alexa, Apple.RTM. Siri, Google.RTM. Now, or
Microsoft.RTM. Cortana.
Mental Health Assistant
[0215] Diabetic patients can be at a high risk for mental health
issues including, for example, stress, depression, anxiety, and
anger. Negative thoughts, feelings, beliefs, and attitudes can
adversely affect the progress of diabetes management. Undiagnosed
and untreated mental health issues can lead to unhealthy diabetes
management habits, which can worsen diabetes prognosis and further
exacerbate mental health issues. In some embodiments, a virtual
health assistant described herein can monitor a user's mental state
and provide psychological support to resolve or reduce the
likelihood of mental health issues.
[0216] A user's mental state can be monitored by analysis of
real-time user biometrics, for example, hormone levels, menstrual
cycles, exercise patterns, sleeping habits, social media presence.
In addition, the virtual health assistant can assess the
psychological state of a user based on user response to mental
health questionnaires. In some embodiments, the virtual health
assistant can connect a user with a health care professional if
determined to be necessary based on the assessment. For example,
the virtual health assistant can provide a communication medium
between a user and a health care professional.
[0217] For example, a virtual health assistant can provide guided
meditation routines as an example mechanism for relieving stress
and promoting healthy psychological state.
Dietary Health Assistant
[0218] Diet and nutrition are critical factors in effective
diabetes management. For example, diabetic patients are recommended
to monitor carbohydrate intake carefully to avoid adverse medical
reactions due to sudden changes in glucose levels in response to
food intake. The virtual health assistant program described herein
can provide a mechanism for monitoring dietary habits of a user
using multimedia devices and systems that monitor user biometrics.
Thus, the system described herein provides a personalized
nutritional guide for health and diet management.
[0219] For example, users can record or log daily food intake using
the system described. User food intake can be recorded in the
system by manual input by the user of descriptions, keywords,
photographs, videos, social media, or other types of multimedia.
The input can be time-stamped and date-stamped to associate the
food intake to a specific time. Accordingly, the system can create
a timeline of user food intake.
[0220] User food intake data can also be associated with one or
more biometrics of the user in real-time before, during, and after
intake of the food. For example, consumption of a high carbohydrate
food by a user can lead to a rapid spike in blood glucose level in
the user. Accordingly, the system can associate the metabolic
effect of a food to a user based on changes to the user's
biometrics following consumption of the food. Over time, the system
can learn and predict future metabolic effects in a user in
response to consumption of a particular food by the user.
[0221] In some embodiments, the user food metabolism data can be
used to provide dietary recommendations to the user. For example,
if the system detects that user consumption of a high carbohydrate
containing food leads to a spike in glucose levels, the system can
provide a future recommendation to the user to consume a lower
carbohydrate containing food.
[0222] In some embodiments, the system can associate a food intake
data with a user's schedule or calendar. For example, if the system
detects that a user has a scheduled exercise, the system can
recommend to the user prior to the scheduled exercise to consume a
food due to the anticipated decrease in glucose level of the user
during exercise. If the system detects that a user has a scheduled
meal, the system can recommend to the user prior to the scheduled
meal to administer insulin due to the anticipated increase in
glucose level of the user during the meal. For example, if a user
has a series of meetings that may intervene with predicted glucose
levels, the system can recommend to the user to consume a snack at
a pre-determined time to reduce the likelihood of a predicted
reduction in glucose levels at a future time point. The
pre-determined time can be predicted by the system based on
historical monitoring of metabolic rates or real-time biometrics of
the user.
[0223] In some embodiments, the system can associate a food intake
data with a user's health goals. For example, a user can have a
goal of losing weight over a period of time. The system can
determine a feasible dietary regimen and eating schedule to meet
the user's goal by analyzing real-time biometrics of the user and
lifestyle habits of the user. For example, lifestyle habits can
include dietary habits, dietary preferences, exercise habits,
sleeping habits, work schedule, and hobbies. For example, for a
user who typically consumes large meals a few times a day, the
system can recommend eating smaller meals and more frequently. For
example, if the system detects that a user has a scheduled
vacation, the system can recommend to the user to take a walk or a
jog to sightsee. The system can recommend a specific tourist route.
For example, if the system detects that a user is dining at a
specific restaurant, the system can recommend to the user specific
food recommendations based on the nutritional facts of menu items
at the restaurant. For example, the system can recommend choosing
more healthful, nutrient-dense foods that promote weight loss or
control glycemic levels.
[0224] Food multimedia received from the user can be analyzed and
evaluated based on a food database that estimates nutritional
content and caloric content based on portion size and nutritional
facts. For example, the system can estimate carbohydrate content of
a food to monitor the effect on the glucose level in the user after
consumption of the food by the user. In some embodiments, the
system can access nutritional facts of restaurant menus or grocery
items from online databases.
[0225] In some embodiments, the system can predict the carbohydrate
content of a food based on multimedia received from the user. For
example, the user can upload a photograph or video of a food
consumed or to be consumed by the user. The system can analyze the
multimedia depiction of the food and determine nutritional content,
for example, carbohydrate content.
[0226] Further, the system described herein can provide a
nutritional rating of a food based on the predicted nutritional
content. Based on historical biometric measurements of the user
after consumption of the food or food having similar nutritional
content, the system can further provide a nutritional rate of the
food or provide a recommendation to the user whether or not to
consume the food.
Improving Patient Adherence
[0227] Patient adherence to treatment regimens is a common issue
among diabetes patients, which can make glycemic control difficult
to attain. Inability to adhere to treatment recommendations
increases the risk of diabetes complications. However, adherence to
treatment regimens can be challenging because diabetes is a
complex, dynamic disease that varies based on patient genetics and
lifestyle choices, for example, dietary habits to exercise habits
to psychological factors. Thus, collaborative systems for managing
diabetes are needed to improve therapeutic efficacy for diabetes
patients. Systems and methods disclosed herein can incite a
behavioral change in a user of the systems or methods. Non-limiting
examples of behavioral change include exercise compliance, dietary
compliance, and medication compliance.
[0228] Diabetes management systems and methods disclosed herein
provide an integrated and supportive system to help diabetics
maintain a healthful lifestyle and achieve personal health goals.
These systems and methods can help diabetics, for example, monitor
blood glucose levels, manage glycemic index, keep track of dietary
habits, adhere to regular exercise recommendations, provide medical
knowledge, reduce stress associated with chronic disease
management, and maintain psychological well-being. As a result,
systems and method disclosed herein empower patients to take
control of their disposition and encourage feelings of independence
and positivity, which, in turn, helps improve patient adherence to
treatment regimens. Implementation of systems and methods disclosed
herein over a time period can result in measurable improvements to
rates of patient adherence to recommended diabetes health protocols
compared to patient adherence prior to implementation of the
systems and methods.
[0229] For example, implementation of systems and methods disclosed
herein over a period of one month can result in at least about 10%,
about 20%, about 30%, about 40%, about 50%, about 60%, about 70%,
about 80%, about 90%, about 100%, about 150%, about 200%, about
250%, about 300%, about 350%, about 400%, about 450%, about 500%,
or greater improvement in patient adherence to recommended diabetes
health protocols compared to patient adherence prior to
implementation of the systems and methods.
External Devices
[0230] In some embodiments, the interactive exercise systems and
methods disclosed herein can be integrated with diabetes-monitoring
devices. Diabetes-monitoring devices can include, for example,
smart watches, glucose monitoring devices, and pulse oximeters.
Non-limiting examples of CGM devices include glucose sensing
patches (e.g. FreeStyle Libre.RTM.), glucose sensing earlobe clips
(e.g. GlucoWatch.RTM.), subcutaneous implants (e.g.
Eversense.RTM.), and smart contact lens. In some embodiments, the
glucose monitoring device is an electronic intraocular device, for
example, electronic contact lenses that monitor glucose levels in a
subject by sensing glucose levels in ocular fluid. CGM devices can
measure glucose by ultrasonic waves, electromagnetic waves, thermal
waves, radio waves, chemical reactions (e.g. fluorescent glucose
polymer technology), and laser technology. Diabetes-monitoring
devices can be invasive or non-invasive devices.
EXAMPLES
Example 1. Use of Algorithms for Diabetes Exercise Therapy to
Improve Diabetic Outcomes
[0231] A subject was a 52 year-old male diagnosed with type-2
diabetes for about 8 years. Prior to beginning the exercise
therapy, the subject was on a combination anti-diabetic therapy
comprising injection with insulin. The subject engaged in exercise
guidance based on the methods disclosed herein, including exercise
suggestions based on desired diabetes metrics outcomes, including
A1C reduction, weight loss, and reduction of anti-diabetic
medication usage. Having engaged the exercises based on the methods
disclosed herein, the subject achieved several diabetes metrics
outcomes, including: a reduction of A1C from about 9.3% to about
6.0%; a weight loss of 58 pounds; and a reduction of insulin
therapy from 116 units per day to about 59 units per day.
Example 2. Use of Algorithms for Diabetes Exercise Therapy to
Improve Diabetic, Cardiovascular, and Pulmonary Outcomes
[0232] A subject was an elderly male that was diagnosed with type-2
diabetes and required an oxygen tank for breathing. Several years
prior to beginning the exercise therapy, the subject had
experienced substantial liver failure that limited the ability of
the subject to exercise. The subject engaged in exercise guidance
based on the methods disclosed herein, including exercise
suggestions based on desired diabetic, cardiovascular, and
pulmonary outcomes and capacities of the subject. Non-limiting
examples of such outcomes include increased muscle tone, increased
cardiac stress resistance, increased lung function, and increased
sexual function.
Example 3. Use of Algorithms for Design of Targeted Type-1 Diabetes
Exercise Therapy and Insulin Administration
[0233] A subject is a 31 year-old female diagnosed with type-1
diabetes for 26 years. The subject measures a glucose level with a
continuous glucose monitoring device and enters a resting glucose
level reading into the application. The resting glucose level is
128 mg/dL. The subject selects a desired diabetes outcome in the
application of A1C goal. The subject receives instruction for an
exercise routine to be performed in a gym based upon weight lifting
selected to create an active heart rate from 90% to 100% of the
maximum heart rate of the subject. The maximum heart rate is
estimated by subtracting the age of the subject from 220, to yield
a maximum heart rate of 188 beats per minute (bpm).
[0234] As the instructed exercise routine creates an active heart
rate from 90% to 100% of the maximum heart rate of the subject,
which increases the glucose level of the subject, the application
suggests adjusting the dose of insulin from a basal rate of 1 unit
per hour (U/h) to an adjusted rate of 1.2 U/h. The application
further utilizes real-time data from biometric devices, including a
heart rate monitor and a continuous glucose monitoring device, to
make further suggestions in real time related to the desired
diabetes outcome, including changes in routine, and warnings to
stop and or test blood sugar, or changes in hormone
administration.
Example 4. Use of Algorithms for Real-Time Tracking of Type-2
Diabetes Exercise Therapy
[0235] A subject is a 47 year-old female diagnosed with type-2
diabetes for 3 years. The subject is currently taking the oral
medication metformin. The subject measures a glucose level with a
single-point glucose monitoring device and enters a resting glucose
level reading into the application. The resting glucose level is
150 mg/dL. The subject selects a desired diabetes outcome in the
application of real-time reduction of blood glucose levels. The
subject enters a critical glucose range of 100 mg/dL to 250 mg/dL.
The subject receives instruction for a lower body cardiovascular
exercise, such as jogging on a treadmill; cycling on a stationary
bicycle; or running on an elliptical, utilizing slow twitch muscle
fibers for 25 minutes. The exercise routine is selected to create
an active heart rate from 60% to 70% of the maximum heart rate of
the subject. The maximum heart rate was estimated by multiplying
the age of the subject by 0.7 and subtracting the value from 208,
to yield a maximum heart rate of 175.1 bpm. The application
utilizes real-time data from biometric devices, including an
activity tracker that monitors calorie expenditure and the
single-point glucose monitoring device.
[0236] Based upon a reading of the glucose level from the
single-point glucose monitoring device that the glucose level of
the subject is below the critical glucose range, the application
provides a warning to the subject in real time to stop the exercise
routine and consume a carbohydrate to restore the glucose level to
within the critical glucose range. Upon consumption of a
fast-acting glucose chewable, the subject re-tests the glucose
level with the single-point glucose monitoring device, which is
transmitted to the application. Upon reading of the glucose level
within the critical glucose range, the application suggests
continuing the brisk walk with continued monitoring of the glucose
level.
Example 5. Use of Algorithms for Real-Time Modification of Type-2
Diabetes Exercise Therapy
[0237] A subject is a 52 year-old male diagnosed with type-2
diabetes for 7 years. The subject has previously performed several
exercise routines based upon the suggestions of the application.
The subject measures a glucose level with a blood glucose meter and
enters a resting glucose level reading into the application. The
resting glucose level is 110 mg/dL. The subject selects a desired
diabetes outcome in the application of increased fat metabolism.
The subject receives instruction from the application for an
exercise routine based on high-intensity interval training combined
with weight lifting selected to create an active heart rate from
90% to 100% of the maximum heart rate of the subject. The maximum
heart rate of the subject has previously been measured through the
treadmill test to be 172 bpm.
[0238] The application utilizes real-time data from biometric
devices, including a heart rate monitoring device and the blood
glucose meter. Based upon a reading of the glucose level from the
blood glucose meter that the glucose level of the subject is above
the critical glucose range of 100 mg/dL to 140 mg/dL, the
application provides a warning to the subject in real time to stop
the current exercise routine of high-intensity interval training
combined with weight lifting. The application suggests an exercise
routine based upon cycling on an exercise bicycle, along with
re-testing of the glucose level with the blood glucose meter, to
restore the glucose level to within the critical glucose range. The
subject stops the current exercise routine of high-intensity
interval training combined with weight lifting and begins the
suggested exercise routine of cycling on the exercise bicycle. The
subject further re-tests the glucose level with the blood glucose
meter device, which is transmitted to the application. Upon reading
of the glucose level within the critical glucose range, the
application suggests returning to the initial exercise routine of
high-intensity interval training combined with weight lifting,
along with continued monitoring of the glucose level.
Example 6. Use of Algorithms for Type-1 Diabetes Exercise Therapy
and Real-Time Modification of Insulin and Glucagon Administration
in a Closed-Loop System
[0239] A subject is a 28 year-old male diagnosed with type-1
diabetes for 23 years. The subject uses a closed-loop system
including a continuous glucose monitoring device, a dual
insulin/glucagon pump contained within a common housing, and a
telecommunications device. The continuous glucose monitoring device
transmits a resting glucose level reading into the application on
the telecommunications device. The resting glucose level is 139
mg/dL. The subject selects a desired diabetes outcome in the
application of A1C reduction. The subject receives instruction for
an exercise routine to be performed with an exercise instruction
video to reach a target heart rate from 60% to 70% of the maximum
heart rate of the subject. The subject sets the critical glucose
range to be from 100 mg/dL to 140 mg/dL. The maximum heart rate is
estimated by subtracting the age of the subject from 220, to yield
a maximum heart rate of 192 bpm.
[0240] As the instructed exercise routine creates an active heart
rate from 60% to 70% of the maximum heart rate of the subject,
which decreases the glucose level of the subject, the application
suggests adjusting the dose of insulin from a basal rate of 1 U/h
to an adjusted rate of 0.9 U/h and adjusting the dose of glucagon
from a basal rate of 0.4 U/h to an adjusted rate of 0.5 U/h. The
application further utilizes real-time data from the continuous
glucose monitoring device of the closed-loop system and displays
the glucose level readings with the exercise instruction video in
real time. During the exercise instruction video, the glucose level
rises above the critical glucose range, which is displayed on the
exercise instruction video. The closed-loop system responds to the
glucose level reading to increase the rate of the dose of insulin
to 0.95 U/h and decrease the rate of the dose of glucagon to 0.45
U/h. The closed-loop system continues to monitor the glucose level
with the continuous glucose monitoring device, transmitting the
readings to the application and displaying the readings on the
exercise instruction video.
Example 7. Interactive Diabetes Exercise Program Dashboard
[0241] FIG. 9 shows an example display of the main page dashboard
of the interactive exercise program.
[0242] The main menu icon (1) slides open from the left side of the
display when selected by the user. The main menu icon leads the
user to various menu tabs that provide user options. User options
can include, for example, accessing user profile, data settings,
and messages.
[0243] The program/workout calendar icon (2) can slide open from
the right side of the display when selected by the user. The
program/workout calendar icon opens a specific program designed for
the user. The workouts can be outlined week by week.
[0244] The Hours below Live Workout icon (3) can be used to search
a specific Live Workout video based on start time. The bar works as
slider that moves from left to right. The user can select a
specific Live Workout video by selecting the start time. The right
panel shows a zoomed out schematic of videos that can be selected
when the user scrolls up and down.
[0245] FIG. 10 shows an example display of the main page dashboard
of the interactive exercise program when the main menu icon (1)
shown in FIG. 9 is selected. The menu bar can display a user
profile image (1) and the number of workouts completed by the user.
Menu options (2) can provide specific functions for the user. Menu
options can include, for example, account information, user
biometric data, user profile, support options, outdoor exercise
routines, settings, messages, and live on-demand exercise routines.
User can access live or recorded media (3), for example, live
on-demand routines, podcasts, and other information about the
program. The logout icon (4) allows users to log off of an
account.
[0246] FIG. 11 shows an example display of the main page dashboard
of the interactive exercise program. User can display a calendar of
the program (5) to track user progress. Highlighted dates can
indicate user completion of exercises. In the calendar interface,
the user can view the week of a program (6) that details a specific
workout routine and completion status. As the user completes a
workout, the program automatically checks off the completed box (7)
to indicate completion. The right panel shows a zoomed out
schematic of detailed weekly exercise routines and completion
status that can be viewed when the user scrolls up and down.
[0247] FIG. 12 shows an example display of the workout pages. The
workout pages can be accessed from the main page dashboard. When a
user selects a desired workout, the workout pages are displayed.
The workout information pages (2) can provide detailed information
about the workout, for example, level of difficulty, duration,
exercise type, performance location (e.g., outdoors or at home). To
begin an exercise, a user can select the start button (1).
Example 8. Targeted Advertising Using Real-Time Biometrics
[0248] A system of the invention is used to detect a user's
biometrics during performance of a physical exercise. The exercise
can be based on an instructional exercise provided by the system,
for example, a biometrics-driven exercise program described
herein.
[0249] A system of the invention monitors a diabetic patient's
real-time biometrics while the patient is performing a high
intensity aerobic exercise. The system can monitor, for example,
the patient's heart rate, blood glucose level, insulin level, and
lipoprotein levels. The system can detect that the patient is
nearing completion of the exercise and will likely require
consumption of a food or beverage to restore blood glucose levels
to normal. In response, the system can present to the patient an
advertisement for a food, for example, an energy beverage.
[0250] A system of the invention monitors a diabetic patient's
real-time biometrics and detects an abnormal rate of decrease in
blood glucose level in the patient. In response, the system can
present to the patient an advertisement for a food product that
would reduce the likelihood of such precipitous variations in blood
glucose level in the future. The system can provide recommendations
for a product or service that can guide the patient on dosing and
administration of a medication. Changes in the patient's biometrics
can also trigger the system to present to the patient different
types of wearable devices, equipment, or programs that relate to
monitoring, controlling, and managing biometric conditions.
[0251] The system can also detect shopping habits of the user. For
example, the system detects that a user that purchases blood
glucose test strips. In response, the system can present to the
patient advertisements for products or services related to
diabetes.
Example 9. Virtual Health Assistant Using Real-Time Biometrics
[0252] A user of the system is a type-2 diabetic patient
recommended to modify lifestyle habits to increase insulin
sensitivity and lose weight by performing regular exercise and
adjusting dietary habits. The system can monitor the patient's
daily exercise and dietary habits, and provide step-by-step
instruction and performance feedback.
[0253] The system can detect that a patient is skipping the
instructional exercises recommended by the instructional exercise
system, for example, due to schedule conflicts. The system can
recommend a tailored exercise schedule for the patient to adhere to
the exercise recommendations. For a patient who does not have time
to exercise during the week due to a work schedule, the system can
recommend that the patient take a certain route to work to increase
activity levels, for example, walking instead of taking the bus or
taking stairs instead of taking the elevator.
[0254] The system can detect the patient's location to recommend
local restaurant options or types of foods that are compatible with
the patient's health goals. The patient can monitor dietary habits
by taking photos or videos of meals or providing descriptions of
nutritional content of meals if available. For example, the patient
can upload an image of a cheeseburger. The system can provide
estimated nutritional facts of the cheeseburger based on the image
provided by the patient. The system can monitor the metabolic
effect of the cheeseburger on the patient by detecting biometrics
over time, for example, blood glucose level after consumption. The
system can recommend alternative food options that are more
compatible with personal taste preferences of the patient based on
detected dietary habits, as well as the patient's health goals. For
example, the system can learn that a cheeseburger results in
elevated triglyceride levels, elevated blood glucose levels, and
reduced insulin sensitivity. Thus, consumption of a cheeseburger is
not incompatible with the patient's prescribed health
recommendation. As a result, the system can suggest a cheeseburger
alternative that has reduced fat and calorie content. Over time,
the system can progressively influence the patient to make more
healthful choices to achieve the patient's health goals.
[0255] FIG. 18 illustrates a computer system 1800 programmed or
otherwise configured to allow monitoring of a biometric of a
subject by biometric sensors 1806 or external biometric devices
1814, present an instructional exercise by instructional exercise
module 1808, and optionally present an advertisement by the
advertisement module 1809, determine subject eligibility in a
clinical trial by the clinical trial module 1810, provide health
guidance by the virtual health module 1811, provide nutritional
health guidance by the nutritional health module 1812, or provide
mental health guidance by the mental health module 1813, in
accordance with various embodiments of the disclosure. The computer
system 1800 includes a server 1802, a CPU 1803, a memory 1804, a
storage unit 1805, biometric sensors 1806, and a communication
interface 1807.
EMBODIMENTS
Embodiment 101
[0256] A method comprising: a) administering to a subject a basal
dose of insulin, wherein the subject is in need thereof, and
wherein the subject is diabetic; b) subsequent to the administering
to the subject the basal dose of insulin, administering to the
subject an adjusted dose of insulin, wherein the adjusted dose of
insulin is from about 5% to about 95% of the basal dose of insulin;
c) subsequent to the administering to the subject the adjusted dose
of insulin, sustaining the subject's heart rate at a level that is
from 10%-50% of the subject's maximum heart rate for at least 30
minutes; and d) subsequent to the sustaining the subject's heart
rate at the level that is from 10%-50% of the subject's maximum
heart rate for at least 30 minutes, elevating the subject's heart
rate to a level that is at least 50% of the subject's maximum heart
rate.
Embodiment 102
[0257] The method of embodiment 101, wherein the subject has type-1
diabetes.
Embodiment 103
[0258] The method of embodiment 101, wherein the subject has type-2
diabetes.
Embodiment 104
[0259] The method of any one of embodiments 101-103, further
comprising administering glucagon to the subject.
Embodiment 105
[0260] The method of any one of embodiments 101-104, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the subject's heart rate is elevated to 50-60% of the subject's
maximum heart rate.
Embodiment 106
[0261] The method of any one of embodiments 101-104, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the subject's heart rate is elevated to 60-70% of the subject's
maximum heart rate.
Embodiment 107
[0262] The method of any one of embodiments 101-104, wherein the
adjusted dose of insulin is about 50% of the basal dose of insulin,
and the subject's heart rate is elevated to 70-80% of the subject's
maximum heart rate.
Embodiment 108
[0263] The method of any one of embodiments 101-104, wherein the
adjusted dose of insulin is about 85% of the basal dose of insulin,
and the subject's heart rate is elevated to 80-90% of the subject's
maximum heart rate.
Embodiment 109
[0264] The method of any one of embodiments 101-104, wherein the
adjusted dose of insulin is about 90% of the basal dose of insulin,
and the subject's heart rate is elevated to 90-100% of the
subject's maximum heart rate.
Embodiment 110
[0265] The method of any one of embodiments 101-109, wherein the
basal dose of insulin and the adjusted dose of insulin are
administered to the subject via an external medical device.
Embodiment 111
[0266] The method of any one of embodiments 101-110, wherein the
basal dose of insulin and the adjusted dose of insulin are
administered to the subject via an insulin pump.
Embodiment 112
[0267] The method of any one of embodiments 101-111, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate for at least 60 minutes.
Embodiment 113
[0268] The method of any one of embodiments 101-112, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate by promoting a state of
physical rest for the subject.
Embodiment 114
[0269] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject.
Embodiment 115
[0270] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by presenting to the subject an exercise instruction via
an electronic communication medium.
Embodiment 116
[0271] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by presenting to the subject an exercise instruction via
an electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject.
Embodiment 117
[0272] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by presenting to the subject an exercise instruction via
an electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; and 2) displays the reading of the biometric
parameter on the electronic communication medium.
Embodiment 118
[0273] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by presenting to the subject an exercise instruction via
an electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; and 2) determines based on the biometric
parameter the suitability at the time point for the subject of an
exercise instruction presented to the subject.
Embodiment 119
[0274] The method of any one of embodiments 101-113, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by presenting to the subject an exercise instruction via
an electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; 2) determines based on the biometric parameter
that an exercise instruction presented to the subject is unsuitable
for the subject at the time point; 3) alerts the subject that the
biometric parameter has deviated from a target range; 4) stops the
presentation of the electronic communication medium; and 5)
presents to the subject, based on the biometric parameter, an
alternative electronic communication medium that provides an
alternative exercise instruction that is suitable for the
subject.
Embodiment 120
[0275] The method of any one of embodiments 116-119, wherein the
biometric device monitors the subject's glucose level.
Embodiment 121
[0276] The method of any one of embodiments 116-120, wherein the
biometric device monitors the subject's heart rate.
Embodiment 122
[0277] The method of any one of embodiment 115-121, wherein the
electronic communication medium is a video.
Embodiment 201
[0278] A method comprising: a) administering to a subject a basal
dose of insulin, wherein the subject is in need thereof, and
wherein the subject is diabetic; b) receiving from the subject a
selection of an exercise that the subject is to perform; c)
determining based on the exercise that the subject is to perform an
adjusted dose of insulin for administration to the subject, wherein
the adjusted dose of insulin is from about 5% to about 95% of the
basal dose of insulin; d) administering to the subject the adjusted
dose of insulin; e) subsequent to the administering to the subject
the adjusted dose of insulin, sustaining the subject's heart rate
at a level that is from 10%-50% of the subject's maximum heart rate
for at least 30 minutes; and f) subsequent to the sustaining the
subject's heart rate at the level that is from 10%-50% of the
subject's maximum heart rate for at least 30 minutes, monitoring
the subject's heart rate to detect an elevation in the subject's
heart rate, wherein the elevation in the subject's heart rate is to
a level that is at least 50% of the subject's maximum heart
rate.
Embodiment 202
[0279] The method of embodiment 201, wherein the subject has type-1
diabetes.
Embodiment 203
[0280] The method of embodiment 201, wherein the subject has type-2
diabetes.
Embodiment 204
[0281] The method of any one of embodiments 201-203, further
comprising administering glucagon to the subject.
Embodiment 205
[0282] The method of any one of embodiments 201-204, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the elevation in the subject's heart rate is to 50-60% of the
subject's maximum heart rate.
Embodiment 206
[0283] The method of any one of embodiments 201-204, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the elevation in the subject's heart rate is to 60-70% of the
subject's maximum heart rate.
Embodiment 207
[0284] The method of any one of embodiments 201-204, wherein the
adjusted dose of insulin is about 50% of the basal dose of insulin,
and the elevation in the subject's heart rate is to 70-80% of the
subject's maximum heart rate.
Embodiment 208
[0285] The method of any one of embodiments 201-204, wherein the
adjusted dose of insulin is about 85% of the basal dose of insulin,
and the elevation in the subject's heart rate is to 80-90% of the
subject's maximum heart rate.
Embodiment 209
[0286] The method of any one of embodiments 201-204, wherein the
adjusted dose of insulin is about 90% of the basal dose of insulin,
and the elevation in the subject's heart rate is to 90-100% of the
subject's maximum heart rate.
Embodiment 210
[0287] The method of any one of embodiments 201-209, wherein the
basal dose of insulin and the adjusted dose of insulin are
administered to the subject via an external medical device.
Embodiment 211
[0288] The method of any one of embodiments 201-209, wherein the
basal dose of insulin and the adjusted dose of insulin are
administered to the subject via an insulin pump.
Embodiment 212
[0289] The method of any one of embodiments 201-211, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate for at least 60 minutes.
Embodiment 213
[0290] The method of any one of embodiments 201-212, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate by promoting a state of
physical rest for the subject.
Embodiment 214
[0291] The method of any one of embodiments 201-213, further
comprising presenting to the subject an exercise instruction via an
electronic communication medium.
Embodiment 215
[0292] The method of any one of embodiments 201-213, further
comprising presenting to the subject an exercise instruction via an
electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject.
Embodiment 216
[0293] The method of any one of embodiments 201-213, further
comprising presenting to the subject an exercise instruction via an
electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; and 2) displays the reading of the biometric
parameter on the electronic communication medium.
Embodiment 217
[0294] The method of any one of embodiments 201-213, further
comprising presenting to the subject an exercise instruction via an
electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; and 2) determines based on the biometric
parameter the suitability at the time point for the subject of an
exercise instruction presented to the subject.
Embodiment 218
[0295] The method of any one of embodiments 201-213, further
comprising presenting to the subject an exercise instruction via an
electronic communication medium, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; 2) determines based on the biometric parameter
that an exercise instruction presented to the subject is unsuitable
for the subject at the time point; 3) alerts the subject that the
biometric parameter has deviated from a target range; 4) stops the
presentation of the electronic communication medium; and 5)
presents to the subject, based on the biometric parameter, an
alternative electronic communication medium that provides an
alternative exercise instruction that is suitable for the
subject.
Embodiment 219
[0296] The method of any one of embodiments 215-218, wherein the
biometric device monitors the subject's glucose level.
Embodiment 220
[0297] The method of any one of embodiments 215-218, wherein the
biometric device monitors the subject's heart rate.
Embodiment 221
[0298] The method of any one of embodiments 214-220, wherein the
electronic communication medium is a video.
Embodiment 301
[0299] A method comprising: a) receiving by a subject a basal dose
of insulin, wherein the subject is in need thereof, and wherein the
subject is diabetic; b) subsequent to the receiving the basal dose
of insulin, receiving by the subject an adjusted dose of insulin,
wherein the adjusted dose of insulin is from about 5% to about 95%
of the basal dose of insulin; c) subsequent to the receiving by the
subject the adjusted dose of insulin, sustaining by the subject the
subject's heart rate at a level that is from 10%-50% of the
subject's maximum heart rate for at least 30 minutes; and d)
subsequent to the sustaining the subject's heart rate at the level
that is from 10%-50% of the subject's maximum heart rate for at
least 30 minutes, elevating by the subject the subject's heart rate
to a level that is at least 50% of the subject's maximum heart
rate.
Embodiment 302
[0300] The method of embodiment 301, wherein the subject has type-1
diabetes.
Embodiment 303
[0301] The method of embodiment 301, wherein the subject has type-2
diabetes.
Embodiment 304
[0302] The method of any one of embodiments 301-303, further
comprising receiving a dose of glucagon by the subject.
Embodiment 305
[0303] The method of any one of embodiments 301-304, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the subject's heart rate is elevated to 50-60% of the subject's
maximum heart rate.
Embodiment 306
[0304] The method of any one of embodiments 301-304, wherein the
adjusted dose of insulin is about 15% of the basal dose of insulin,
and the subject's heart rate is elevated to 60-70% of the subject's
maximum heart rate.
Embodiment 307
[0305] The method of any one of embodiments 301-304, wherein the
adjusted dose of insulin is about 50% of the basal dose of insulin,
and the subject's heart rate is elevated to 70-80% of the subject's
maximum heart rate.
Embodiment 308
[0306] The method of any one of embodiments 301-304, wherein the
adjusted dose of insulin is about 85% of the basal dose of insulin,
and the subject's heart rate is elevated to 80-90% of the subject's
maximum heart rate.
Embodiment 309
[0307] The method of any one of embodiments 301-304, wherein the
adjusted dose of insulin is about 90% of the basal dose of insulin,
and the subject's heart rate is elevated to 90-100% of the
subject's maximum heart rate.
Embodiment 310
[0308] The method of any one of embodiments 301-309, wherein the
subject receives the basal dose of insulin and the adjusted dose of
insulin via an external medical device.
Embodiment 311
[0309] The method of any one of embodiments 301-309, wherein the
subject receives the basal dose of insulin and the adjusted dose of
insulin via an insulin pump.
Embodiment 312
[0310] The method of any one of embodiments 301-311, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate for at least 60 minutes.
Embodiment 313
[0311] The method of any one of embodiments 301-312, wherein the
subject's heart rate is sustained at a level that is from 10%-50%
of the subject's maximum heart rate by a state of physical
rest.
Embodiment 314
[0312] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by a state of physical
exercise.
Embodiment 315
[0313] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by a state of physical exercise,
wherein the state of physical exercise is promoted by receiving by
the subject an electronic communication medium that provides
exercise instruction.
Embodiment 316
[0314] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by a state of physical exercise,
wherein the state of physical exercise is promoted by receiving by
the subject an electronic communication medium that provides
exercise instruction, wherein the electronic communication medium
is processed by a computer system that is in communication with a
biometric device that is in contact with the subject.
Embodiment 317
[0315] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by promoting a state of physical
exercise for the subject, wherein the state of physical exercise is
promoted by receiving by the subject an electronic communication
medium that provides exercise instruction, wherein the electronic
communication medium is processed by a computer system that is in
communication with a biometric device that is in contact with the
subject, wherein the computer system: 1) receives a reading of a
biometric parameter of the subject at a time point from the
biometric device; and 2) communicates the reading of the biometric
parameter to the subject.
Embodiment 318
[0316] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by a state of physical exercise,
wherein the state of physical exercise is promoted by receiving by
the subject an electronic communication medium that provides
exercise instruction, wherein the electronic communication medium
is processed by a computer system that is in communication with a
biometric device that is in contact with the subject, wherein the
computer system: 1) receives a reading of a biometric parameter of
the subject at a time point from the biometric device; and 2)
determines based on the biometric parameter the suitability at the
time point for the subject of an exercise instruction presented to
the subject.
Embodiment 319
[0317] The method of any one of embodiments 301-313, wherein the
subject's heart rate is elevated to a level that is at least 50% of
the subject's maximum heart rate by a state of physical exercise,
wherein the state of physical exercise is promoted by receiving by
the subject an electronic communication medium that provides
exercise instruction, wherein the electronic communication medium
is processed by a computer system that is in communication with a
biometric device that is in contact with the subject, wherein the
computer system: 1) receives a reading of a biometric parameter of
the subject at a time point from the biometric device; 2)
determines based on the biometric parameter that an exercise
instruction presented to the subject is unsuitable for the subject
at the time point; 3) alerts the subject that the biometric
parameter has deviated from a target range; 4) stops the
presentation of the electronic communication medium; and 5)
presents to the subject, based on the biometric parameter, an
alternative electronic communication medium that provides an
alternative exercise instruction that is suitable for the
subject.
Embodiment 320
[0318] The method of any one of embodiments 301-319, wherein the
subject communicates a selection of an exercise to perform to a
computer system, wherein the computer system determines a level of
the adjusted dose of insulin based on the exercise to perform and a
reading of a biometric device that is in contact with the
subject.
Embodiment 321
[0319] The method of embodiment 320, wherein the subject receives
exercise instruction from the computer system based on the exercise
to perform and the reading of the biometric device that is in
contact with the subject.
Embodiment 322
[0320] The method of any one of embodiments 315-321, wherein the
electronic communication medium is a video.
Embodiment 323
[0321] The method of any one of embodiments 316-322, wherein the
biometric device monitors the subject's glucose level.
Embodiment 324
[0322] The method of any one of embodiments 316-323, wherein the
biometric device monitors the subject's heart rate.
Embodiment 325
[0323] The method of any one of embodiments 320-321, wherein the
subject receives from the computer system an indication of the
suitability of the exercise for the subject based on the reading of
the biometric device that is in contact with the subject.
Embodiment 326
[0324] The method of any one of embodiments 320-321, wherein the
subject receives from the computer system an indication that the
exercise is unsuitable for the subject based on the reading of the
biometric device that is in contact with the subject.
Embodiment 327
[0325] The method of any one of embodiments 320-321, wherein the
subject receives from the computer system an instruction to perform
an alternative exercise instruction that is suitable for the
subject based on the reading of the biometric device that is in
contact with the subject.
Embodiment 401
[0326] A system comprising: a) a telecommunications device; b) an
insulin delivery device that is: 1) in contact with a subject; 2)
in communication with the telecommunications device; 3) configured
to administer insulin to the subject; and 4) configured to receive
from the telecommunications device a transmission of an instruction
to administer to the subject a dose of insulin; and c) a glucose
monitoring device that is: 1) in contact with the subject; 2) in
communication with the telecommunications device; 3) configured to
detect a glucose level in the subject; and 4) configured to
transmit to the telecommunications device a reading of the glucose
level in the subject, wherein the telecommunications device sends a
transmission from the telecommunications device to the insulin
delivery device, wherein the transmission instructs the insulin
delivery device to administer to the subject an adjusted dose of
insulin over a period of at least 30 minutes, wherein the adjusted
dose of insulin is from about 5% to about 95% of a basal dose of
insulin for the subject.
Embodiment 402
[0327] The system of embodiment 1, wherein the telecommunications
device is configured to display the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 403
[0328] The system of any one of embodiments 401-402, wherein the
insulin delivery device is configured to adjust an amount of
insulin that is administered to the subject based on the glucose
level detected in the subject by the glucose monitoring device.
Embodiment 404
[0329] The system of any one of embodiments 401-403, wherein the
insulin delivery device and the glucose monitoring device are in a
common housing.
Embodiment 405
[0330] The system of any one of embodiments 401-403, wherein the
insulin delivery device, the glucose monitoring device, and the
telecommunications device are in a common housing.
Embodiment 406
[0331] The system of any one of embodiments 401-403, further
comprising a glucagon delivery device that is: 1) in contact with
the subject; 2) in communication with the telecommunications
device; 3) configured to administer glucagon to the subject; and 4)
configured to receive from the telecommunications device an
instruction to administer to the subject a dose of glucagon.
Embodiment 407
[0332] The system of embodiment 406, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 408
[0333] The system of embodiment 406, wherein the insulin delivery
device, the glucose monitoring device, and the glucagon delivery
device are in a common housing.
Embodiment 409
[0334] The system of embodiment 406, wherein the insulin delivery
device, the glucose monitoring device, the glucagon delivery
device, and the telecommunications device are in a common
housing.
Embodiment 410
[0335] The system of any one of embodiments 406-409, wherein the
glucagon delivery device is configured to adjust an amount of
glucagon that is administered to the subject based on the glucose
level detected in the subject by the glucose monitoring device.
Embodiment 411
[0336] The system of any one of embodiments 401-410, wherein the
transmission from the telecommunications device to the insulin
delivery device instructs the insulin delivery device to administer
to the subject an adjusted dose of insulin over a period of at
least 60 minutes.
Embodiment 412
[0337] The system of any one of embodiments 401-411, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 413
[0338] The system of any one of embodiments 401-411, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 414
[0339] The system of any one of embodiments 401-411, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 415
[0340] The system of any one of embodiments 401-411, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 416
[0341] The system of any one of embodiments 401-415, wherein the
telecommunications device is in communication with a media device,
wherein the telecommunications device instructs the media device to
present to the subject an instructional exercise electronic
communication medium based on the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 417
[0342] The system of embodiment 416, wherein the electronic
communication medium is a video.
Embodiment 418
[0343] The system of any one of embodiments 401-417, wherein the
telecommunications device is configured to determine a level of the
dose of insulin based on an input of an exercise to be performed by
the subject and the reading of the glucose level in the subject by
the glucose monitoring device.
Embodiment 419
[0344] The system of any one of embodiments 401-418, wherein any
device or housing is implanted in the subject.
Embodiment 501
[0345] A system comprising: a) a telecommunications device; b) an
insulin delivery device that is: 1) in contact with a subject; 2)
in communication with the telecommunications device; 3) configured
to administer insulin to the subject; and 4) configured to receive
from the telecommunications device a transmission of an instruction
to administer to the subject a dose of insulin; c) a glucose
monitoring device that is: 1) in contact with the subject; 2) in
communication with the telecommunications device; 3) configured to
detect a glucose level in the subject; and 4) configured to
transmit to the telecommunications device a reading of the glucose
level in the subject; and d) a heart rate monitor device that is:
1) in contact with the subject; 2) in communication with the
telecommunications device; 3) configured to detect a heart rate in
the subject; and 4) configured to transmit to the
telecommunications device a reading of the heart rate in the
subject, wherein the telecommunications device sends a transmission
from the telecommunications device to the insulin delivery device,
wherein the transmission instructs the insulin delivery device,
based on the reading of the heart rate of the subject, to
administer to the subject an adjusted dose of insulin over a period
of at least 30 minutes, wherein the adjusted dose of insulin is
from about 5% to about 95% of a basal dose of insulin for the
subject.
Embodiment 502
[0346] The system of embodiment 501, wherein the telecommunications
device is configured to display the glucose level detected in the
subject by the glucose monitoring device and the heart rate
detected in the subject by the heart rate monitoring device.
Embodiment 503
[0347] The system of any one of embodiments 501-502, wherein the
insulin delivery device is configured to adjust an amount of
insulin that is administered to the subject based on the glucose
level detected in the subject by the glucose monitoring device and
the heart rate detected in the subject by the heart rate monitoring
device.
Embodiment 504
[0348] The system of any one of embodiments 501-503, wherein the
insulin delivery device and the glucose monitoring device are in a
common housing.
Embodiment 505
[0349] The system of any one of embodiments 501-503, wherein the
insulin delivery device, the glucose monitoring device, and the
heart rate monitoring device are in a common housing.
Embodiment 506
[0350] The system of any one of embodiments 501-503, wherein the
insulin delivery device, the glucose monitoring device, and the
telecommunications device are in a common housing.
Embodiment 507
[0351] The system of any one of embodiments 501-503, wherein the
insulin delivery device, the glucose monitoring device, the heart
rate monitoring device, and the telecommunications device are in a
common housing
Embodiment 508
[0352] The system of any one of embodiments 501-507, further
comprising a glucagon delivery device that is: 1) in contact with
the subject; 2) in communication with the telecommunications
device; 3) configured to administer glucagon to the subject; and 4)
configured to receive from the telecommunications device an
instruction to administer to the subject a dose of glucagon.
Embodiment 509
[0353] The system of embodiment 508, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 510
[0354] The system of embodiment 508, wherein the insulin delivery
device, the glucose monitoring device, the heart rate monitoring
device, and the glucagon delivery device are in a common
housing.
Embodiment 511
[0355] The system of embodiment 508, wherein the insulin delivery
device, the glucose monitoring device, the heart rate monitoring
device, the glucagon delivery device, and the telecommunications
device are in a common housing.
Embodiment 512
[0356] The system of embodiment 508, wherein the glucagon delivery
device is configured to adjust an amount of glucagon that is
administered to the subject based on the glucose level detected in
the subject by the glucose monitoring device and the heart rate
detected in the subject by the heart rate monitoring device.
Embodiment 513
[0357] The system of any one of embodiments 501-512, wherein the
transmission from the telecommunications device to the insulin
delivery device instructs the insulin delivery device to administer
to the subject an adjusted dose of insulin over a period of at
least 60 minutes.
Embodiment 514
[0358] The system of any one of embodiments 501-513, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 515
[0359] The system of any one of embodiments 501-513, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 516
[0360] The system of any one of embodiments 501-513, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 517
[0361] The system of any one of embodiments 501-513, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 518
[0362] The system of any one of embodiments 501-517, wherein the
telecommunications device is in communication with a media device,
wherein the telecommunications device instructs the media device to
present to the subject an instructional exercise electronic
communication medium based on the glucose level detected in the
subject by the glucose monitoring device and the heart rate
detected in the subject by the heart rate monitoring device.
Embodiment 519
[0363] The system of embodiment 518, wherein the electronic
communication medium is a video.
Embodiment 520
[0364] The system of any one of embodiments 501-519, wherein the
telecommunications device is configured to determine a level of the
dose of insulin based on an input of an exercise to be performed by
the subject, the reading of the glucose level in the subject by the
glucose monitoring device, and the heart rate detected in the
subject by the heart rate monitoring device.
Embodiment 521
[0365] The system of any one of embodiments 501-520, wherein any
device or housing is implanted in the subject.
Embodiment 601
[0366] A system comprising: a) an insulin delivery device that is:
1) in contact with a subject; 2) configured to administer insulin
to the subject; and 3) configured to receive a transmission of an
instruction to administer to the subject a dose of insulin; and b)
a glucose monitoring device that is: 1) in contact with the
subject; 2) in communication with the insulin delivery device; 3)
configured to detect a glucose level in the subject; and 4)
configured to transmit to the insulin delivery device an
instruction to administer to the subject the dose of insulin based
on the detected glucose level in the subject, wherein the insulin
delivery device comprises a processor and a computer-readable
medium with a computer-executable code encoded thereon, wherein the
computer-executable code instructs the insulin delivery device to
administer to the subject an adjusted dose of insulin over a period
of at least 30 minutes, wherein the adjusted dose of insulin is
from about 5% to about 95% of a basal dose of insulin for the
subject, and wherein the processor processes the
computer-executable code.
Embodiment 602
[0367] The system of embodiment 601, wherein the insulin delivery
device is configured to adjust an amount of insulin that is
administered to the subject based on the glucose level detected in
the subject by the glucose monitoring device.
Embodiment 603
[0368] The system of any one of embodiments 601-602, further
comprising a glucagon delivery device that is: 1) in contact with
the subject; 2) in communication with the insulin delivery device;
3) configured to administer glucagon to the subject; and 4)
configured to receive from the insulin delivery device an
instruction to administer to the subject a dose of glucagon.
Embodiment 604
[0369] The system of embodiment 603, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 605
[0370] The system of any one of embodiments 603-604, wherein the
glucagon delivery device is configured to adjust an amount of
glucagon that is administered to the subject based on the glucose
level detected in the subject by the glucose monitoring device.
Embodiment 606
[0371] The system of any one of embodiments 601-605, wherein the
transmission instructs the insulin delivery device to administer to
the subject an adjusted dose of insulin over a period of at least
60 minutes.
Embodiment 607
[0372] The system of any one of embodiments 601-606, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 608
[0373] The system of any one of embodiments 601-606, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 609
[0374] The system of any one of embodiments 601-606, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 610
[0375] The system of any one of embodiments 601-606, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 611
[0376] The system of any one of embodiments 601-610, further
comprising a telecommunications device that is: 1) in communication
with the insulin delivery device; 2) in communication with the
glucose monitoring device; 3) configured to transmit to the insulin
delivery device an instruction to administer to the subject the
dose of insulin; and 4) configured to receive from the glucose
monitoring device a transmission of a reading of the glucose level
in the subject, wherein the insulin delivery device is configured
to receive from the telecommunications device an instruction to
administer to the subject the dose of insulin; and the glucose
monitoring device is configured to transmit to the
telecommunications device the reading of the glucose level in the
subject.
Embodiment 612
[0377] The system of embodiment 611, wherein the telecommunications
device is configured to display the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 613
[0378] The system of any one of embodiments 611-612, wherein the
telecommunications device is in communication with a media device,
wherein the telecommunications device instructs the media device to
present to the subject an instructional exercise electronic
communication medium based on the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 614
[0379] The system of embodiment 613, wherein the electronic
communication medium is a video.
Embodiment 615
[0380] The system of any one of embodiments 601-614, wherein any
device or housing is implanted in the subject.
Embodiment 701
[0381] A system comprising: a) an insulin delivery device that is:
1) in contact with a subject; 2) configured to administer insulin
to the subject; and 3) configured to receive a transmission of an
instruction to administer to the subject a dose of insulin; and b)
a glucose monitoring device that is: 1) in contact with the
subject; 2) in communication with the insulin delivery device; 3)
configured to detect a glucose level in the subject; and 4)
configured to transmit to the insulin delivery device an
instruction to administer to the subject the dose of insulin based
on the detected glucose level in the subject, wherein the glucose
monitoring device sends a transmission from the glucose monitoring
device to the insulin delivery device, wherein the transmission
instructs the insulin delivery device to administer to the subject
an adjusted dose of insulin over a period of at least 30 minutes,
wherein the adjusted dose of insulin is from about 5% to about 95%
of a basal dose of insulin for the subject.
Embodiment 702
[0382] The system of embodiment 701, wherein the insulin delivery
device is configured to adjust an amount of insulin that is
administered to the subject based on the glucose level detected in
the subject by the glucose monitoring device.
Embodiment 703
[0383] The system of any one of embodiments 701-702, further
comprising a glucagon delivery device that is: 1) in contact with
the subject; 2) in communication with the glucose monitoring
device; 3) configured to administer glucagon to the subject; and 4)
configured to receive from the glucose monitoring device an
instruction to administer to the subject a dose of glucagon.
Embodiment 704
[0384] The system of embodiment 703, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 705
[0385] The system of any one of embodiments 703-704, wherein the
glucagon delivery device is configured to adjust an amount of
glucagon that is administered to the subject based on the glucose
level detected in the subject by the glucose monitoring device.
Embodiment 706
[0386] The system of any one of embodiments 701-705, wherein the
transmission instructs the insulin delivery device to administer to
the subject an adjusted dose of insulin over a period of at least
60 minutes.
Embodiment 707
[0387] The system of any one of embodiments 701-706, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 708
[0388] The system of any one of embodiments 701-706, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 709
[0389] The system of any one of embodiments 701-706, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 710
[0390] The system of any one of embodiments 701-706, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 711
[0391] The system of any one of embodiments 701-710, further
comprising a telecommunications device that is: 1) in communication
with the insulin delivery device; 2) in communication with the
glucose monitoring device; 3) configured to transmit to the insulin
delivery device an instruction to administer to the subject the
dose of insulin; and 4) configured to receive from the glucose
monitoring device a transmission of a reading of the glucose level
in the subject, wherein the insulin delivery device is configured
to receive from the telecommunications device an instruction to
administer to the subject the dose of insulin; and the glucose
monitoring device is configured to transmit to the
telecommunications device the reading of the glucose level in the
subject.
Embodiment 712
[0392] The system of embodiment 711, wherein the telecommunications
device is configured to display the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 713
[0393] The system of any one of embodiments 711-712, wherein the
telecommunications device is in communication with a media device,
wherein the telecommunications device instructs the media device to
present to the subject an instructional exercise electronic
communication medium based on the glucose level detected in the
subject by the glucose monitoring device.
Embodiment 714
[0394] The system of embodiment 713, wherein the electronic
communication medium is a video.
Embodiment 715
[0395] The system of any one of embodiments 701-714, wherein any
device or housing is implanted in the subject.
Embodiment 801
[0396] A kit comprising: a) an insulin delivery device; and b) a
glucose monitoring device, wherein the insulin delivery device
comprises a processor and a computer-readable medium with a
computer-executable code encoded thereon, wherein the
computer-executable code instructs the insulin delivery device to
administer to a subject an adjusted dose of insulin over a period
of at least 30 minutes, wherein the adjusted dose of insulin is
from about 5% to about 95% of a basal dose of insulin for the
subject, and wherein the processor processes the
computer-executable code.
Embodiment 802
[0397] The kit of embodiment 801, further comprising a glucagon
delivery device.
Embodiment 803
[0398] The kit of embodiment 802, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 804
[0399] The kit of any one of embodiments 801-803, wherein the
computer-executable code instructs the insulin delivery device to
administer to a subject the adjusted dose of insulin over a period
of at least 60 minutes.
Embodiment 805
[0400] The kit of any one of embodiments 801-804, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 806
[0401] The kit of any one of embodiments 801-804, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 807
[0402] The kit of any one of embodiments 801-804, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 808
[0403] The kit of any one of embodiments 801-804, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 809
[0404] The kit of any one of embodiments 801-804, further
comprising a telecommunications device.
Embodiment 810
[0405] The kit of embodiment 1, further comprising a heart rate
monitor device.
Embodiment 901
[0406] A kit comprising: a) a telecommunications device; b) an
insulin delivery device; and c) a glucose monitoring device,
wherein the telecommunications device comprises a processor and a
computer-readable medium with a computer-executable code encoded
thereon, wherein the computer-executable code instructs the
telecommunications device to transmit to the insulin delivery
device an instruction to administer to a subject an adjusted dose
of insulin over a period of at least 30 minutes, wherein the
adjusted dose of insulin is from about 5% to about 95% of a basal
dose of insulin for the subject, and wherein the processor
processes the computer-executable code.
Embodiment 902
[0407] The kit of embodiment 901, further comprising a glucagon
delivery device.
Embodiment 903
[0408] The kit of embodiment 902, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 904
[0409] The kit of any one of embodiments 901-903, wherein the
computer-executable code instructs the insulin delivery device to
administer to a subject the adjusted dose of insulin over a period
of at least 60 minutes.
Embodiment 905
[0410] The kit of any one of embodiments 901-904, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 906
[0411] The kit of any one of embodiments 901-904, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 907
[0412] The kit of any one of embodiments 901-904, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 908
[0413] The kit of any one of embodiments 901-904, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 909
[0414] The kit of any one of embodiments 901-908, further
comprising a heart rate monitor device.
Embodiment 1001
[0415] A kit comprising: a) an insulin delivery device; and b) a
glucose monitoring device, wherein the glucose monitoring device
comprises a processor and a computer-readable medium with a
computer-executable code encoded thereon, wherein the
computer-executable code instructs the glucose monitoring device to
transmit to the insulin delivery device an instruction to
administer to a subject an adjusted dose of insulin over a period
of at least 30 minutes, wherein the adjusted dose of insulin is
from about 5% to about 95% of a basal dose of insulin for the
subject, and wherein the processor processes the
computer-executable code.
Embodiment 1002
[0416] The kit of embodiment 1001, further comprising a glucagon
delivery device.
Embodiment 1003
[0417] The kit of embodiment 1002, wherein the insulin delivery
device and the glucagon delivery device are in a common
housing.
Embodiment 1004
[0418] The kit of any one of embodiments 1001-1003, wherein the
computer-executable code instructs the insulin delivery device to
administer to a subject the adjusted dose of insulin over a period
of at least 60 minutes.
Embodiment 1005
[0419] The kit of any one of embodiments 1001-1004, wherein the
adjusted dose of insulin is about 15% of the basal dose of
insulin.
Embodiment 1006
[0420] The kit of any one of embodiments 1001-1004, wherein the
adjusted dose of insulin is about 50% of the basal dose of
insulin.
Embodiment 1007
[0421] The kit of any one of embodiments 1001-1004, wherein the
adjusted dose of insulin is about 85% of the basal dose of
insulin.
Embodiment 1008
[0422] The kit of any one of embodiments 1001-1004, wherein the
adjusted dose of insulin is about 90% of the basal dose of
insulin.
Embodiment 1009
[0423] The kit of any one of embodiments 1001-1008, further
comprising a telecommunications device.
Embodiment 1010
[0424] The kit of any one of embodiments 1001-1009, further
comprising a heart rate monitor device.
Embodiment 1101
[0425] A method comprising: a) presenting by a media device to a
subject an electronic communication medium that provides
instruction for physical exercise, wherein the subject is diabetic,
wherein the media device is in communication with a receiver; b)
monitoring, contemporaneously with presenting to the subject the
electronic communication medium that provides instruction for
physical exercise, via a glucose monitoring device the subject
during a state of physical exercise, wherein the glucose monitoring
device detects a blood glucose level in the subject; c)
transmitting by a biometric device the blood glucose level of the
subject to the receiver; d) receiving by the receiver the blood
glucose level of the subject; and e) presenting by the media device
an indication of a change in the blood glucose level of the subject
in real time contemporaneously with presenting the electronic
communication medium that provides instruction for physical
exercise.
Embodiment 1102
[0426] The method of embodiment 1101, wherein the subject has
type-1 diabetes.
Embodiment 1103
[0427] The method of embodiment 1101, wherein the subject has
type-2 diabetes.
Embodiment 1104
[0428] The method of any one of embodiments 1101-1103, wherein the
electronic communication medium is a video.
Embodiment 1105
[0429] The method of any one of embodiments 1101-1104, further
comprising presenting to the subject by the electronic
communication medium a warning that a biometric parameter of the
subject has reached a value associated with a state of high
risk.
Embodiment 1106
[0430] The method of any one of embodiments 1101-1105, wherein the
receiver is in communication with a processor, wherein the
processor determines based on the blood glucose level of the
subject the suitability for the subject of an exercise instruction
presented to the subject.
Embodiment 1107
[0431] The method of any one of embodiments 1101-1105, wherein the
receiver is in communication with a processor, wherein the
processor determines based on the blood glucose level of the
subject that an exercise instruction being presented to the subject
is unsuitable for the subject, and instructs the media device to
display to the subject an alternative electronic communication
medium that provides an alternative exercise instruction that is
suitable for the subject based on the blood glucose level of the
subject.
Embodiment 1108
[0432] The method of any one of embodiments 1101-1107, further
comprising monitoring the subject's heart rate by a heart rate
monitor, and presenting by the media device an indication of the
subject's heart rate contemporaneously with presenting the
electronic communication medium that provides instruction for
physical exercise.
Embodiment 1109
[0433] The method of embodiment 1108, wherein the receiver is in
communication with a processor, wherein the processor determines
based on the subject's heart rate the suitability for the subject
of an exercise instruction presented to the subject.
Embodiment 1110
[0434] The method of embodiment 1108, wherein the receiver is in
communication with a processor, wherein the processor determines
based on the subject's heart rate that an exercise instruction
being presented to the subject is unsuitable for the subject, and
instructs the media device to display to the subject an alternative
electronic communication medium that provides an alternative
exercise instruction that is suitable for the subject based on the
subject's heart rate.
Embodiment 1111
[0435] The method of any one of embodiments 1101-1110, further
comprising administering to the subject a dose of insulin based on
the blood glucose level of the subject.
Embodiment 1112
[0436] The method of any one of embodiments 1101-1111, further
comprising administering to the subject a dose of glucose based on
the blood glucose level of the subject.
Embodiment 1113
[0437] The method of any one of embodiments 1101-1112, further
comprising administering to the subject a dose of glucagon based on
the blood glucose level of the subject.
Embodiment 1114
[0438] The method of any one of embodiments 1101-1113, further
comprising receiving by the media device an input of a selection by
the subject of an exercise to perform, wherein the presenting by
the media device to the subject the electronic communication medium
that provides the instruction for the physical exercise is based on
the input of the selection by the subject.
Embodiment 1201
[0439] A system comprising: a media device configured to present:
a) an instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) an advertisement electronic communication based on the
biometric measurement detected in the subject.
Embodiment 1202
[0440] The system of embodiment 1201, further comprising a
processor configured to generate the advertisement electronic
communication based on the biometric measurement detected in the
subject, wherein the processor is in communication with the media
device.
Embodiment 1203
[0441] The system of embodiment 1202, further comprising a receiver
configured to receive the biometric measurement detected in the
subject, wherein the receiver is in communication with the media
device.
Embodiment 1204
[0442] The system of embodiment 1203, wherein the media device, the
processor, and the receiver are in a common housing.
Embodiment 1205
[0443] The system of embodiment 1203, wherein the media device, the
processor, the receiver, and the biometric device are in a common
housing.
Embodiment 1206
[0444] The system of any one of embodiments 1201-1205, wherein the
biometric device is: a) in contact with the subject; b) in
communication with the media device; c) configured to detect the
biometric measurement in the subject; and d) configured to transmit
to the media device a reading of the biometric measurement detected
in the subject.
Embodiment 1207
[0445] The system of any one of embodiments 1201-1206, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 1208
[0446] The system of any one of embodiments 1201-1206, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 1209
[0447] The system of any one of embodiments 1201-1208, wherein the
advertisement electronic communication is a clinical trial
enrollment opportunity advertisement associated with the biometric
measurement detected in the subject.
Embodiment 1301
[0448] A method comprising: a) presenting by a media device to a
subject an instructional exercise electronic communication that
provides instruction for physical exercise based on a biometric
measurement detected in the subject by a biometric device; and b)
presenting by the media device to the subject an advertisement
electronic communication that provides an advertisement based on
the biometric measurement detected in the subject.
Embodiment 1302
[0449] The method of embodiment 1301, further comprising detecting
by the biometric device the biometric measurement in the subject,
wherein the biometric device is in contact with the subject.
Embodiment 1303
[0450] The method of embodiment 1302, wherein the detecting of the
biometric measurement in the subject is during a state of physical
exercise.
Embodiment 1304
[0451] The method of any one of embodiments 1301-1303, further
comprising receiving by a receiver from the biometric device a
reading of the biometric measurement detected in the subject,
wherein the receiver is in communication with the media device.
Embodiment 1305
[0452] The method of embodiment 1304, further comprising
transmitting by the biometric device the reading of the biometric
measurement detected in the subject to the receiver.
Embodiment 1306
[0453] The method of any one of embodiments 1301-1305, further
comprising presenting, contemporaneously with presenting the
instructional exercise electronic communication, by the media
device to the subject an indication of a change in the biometric
measurement detected in the subject in real-time by the biometric
device.
Embodiment 1307
[0454] The method of any one of embodiments 1301-1306, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 1308
[0455] The method of any one of embodiments 1301-1306, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 1309
[0456] The method of any one of embodiments 1301-1308, wherein the
subject is diabetic.
Embodiment 1401
[0457] A computer program product comprising a non-transitory
computer-readable medium having computer-executable code encoded
therein, the computer-executable code adapted to be executed to
implement a method of advertising to a subject, the method
comprising: a) processing an advertisement system, wherein the
advertisement system comprises: i) an instructional exercise
communication module; ii) an advertisement communication module;
and iii) an output module; b) generating by the instructional
exercise communication module an instructional exercise
communication based on a reading of a biometric measurement
detected in the subject by a biometric device; c) generating by the
advertisement communication module an advertisement based on the
reading of the biometric measurement detected in the subject; d)
communicating by the output module the instructional exercise
communication to an output media device; and e) communicating by
the output module the advertisement to the output media device.
Embodiment 1402
[0458] The computer program product of embodiment 1401, wherein the
advertisement system further comprises a biometric data receiving
module, and the method further comprises receiving by the biometric
data receiving module the reading of the biometric measurement in
the subject.
Embodiment 1403
[0459] The computer program product of embodiment 1401 or 1402,
wherein the advertisement system further comprises a biometric
detecting module, and the method further comprises detecting by the
biometric detecting module the biometric measurement in the
subject.
Embodiment 1404
[0460] The computer program product of any one of embodiments
1401-1403, wherein the communicating of the advertisement to the
output media device is contemporaneous with the communicating of
the instructional exercise electronic communication to the output
media device.
Embodiment 1501
[0461] A method comprising: a) reviewing by a user from a media
device an instructional exercise electronic communication; b)
performing by the user an exercise suggested by the instructional
exercise electronic communication; and c) receiving by the user
from the media device an advertisement electronic communication
that provides an advertisement based on a biometric measurement
detected in the user by a biometric device.
Embodiment 1502
[0462] A method comprising: a) performing by a user an exercise; b)
receiving by the user from a media device an instructional exercise
electronic communication based on a biometric measurement detected
in the user by a biometric device; and c) receiving by the user
from the media device an advertisement electronic communication
that provides an advertisement based on the biometric measurement
detected in the user by the biometric device.
Embodiment 1503
[0463] The method of embodiment 1501 or 1502, wherein the
advertisement is provided when the biometric measurement detected
in the subject is determined to be unsafe.
Embodiment 1504
[0464] The method of any one of embodiments 1501-1503, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 1505
[0465] The method of any one of embodiments 1501-1503, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 1506
[0466] The method of embodiment 1505, wherein the advertisement is
provided when the heart rate detected in the subject is determined
to be in a zone from 40% to 100% of a maximum heart rate in the
user.
Embodiment 1507
[0467] The method of any one of embodiments 1501-1506, further
comprising selecting by the user on the media device the received
advertisement electronic communication.
Embodiment 1508
[0468] The method of any one of embodiments 1501-1507, further
comprising purchasing by the user a product or a service described
in the received advertisement.
Embodiment 1509
[0469] The method of any one of embodiments 1501-1508, wherein the
advertisement is provided during the performing of the exercise by
the user.
Embodiment 1510
[0470] The method of any one of embodiments 1501-1508, wherein the
advertisement is provided before the performing of the exercise by
the user.
Embodiment 1511
[0471] The method of any one of embodiments 1501-1508, wherein the
advertisement is provided after the performing of the exercise by
the user.
Embodiment 1512
[0472] The method of any one of embodiments 1501-1511, wherein the
user is diabetic.
Embodiment 1601
[0473] A system comprising: a) a heart rate monitoring device
configured to detect a heart rate in a subject; and b) a media
device configured to present an advertisement electronic
communication based on the heart rate detected in the subject by
the heart rate monitoring device, wherein the heart rate monitoring
device is configured to transmit to the media device a reading of
the heart rate in the subject, wherein the media device is
configured to present the advertisement electronic communication
upon determination that the heart rate in the subject detected by
the heart rate monitoring device is in a zone from 40% to 100% of a
maximum heart rate in the subject.
Embodiment 1602
[0474] The system of embodiment 1601, further comprising a
processor configured to generate the advertisement electronic
communication based on the heart rate detected in the subject,
wherein the processor is in communication with the media
device.
Embodiment 1603
[0475] The system of embodiment 1602, further comprising a receiver
configured to receive the heart rate detected in the subject,
wherein the receiver is in communication with the media device.
Embodiment 1604
[0476] The system of embodiment 1603, wherein the media device, the
processor, and the receiver are in a common housing.
Embodiment 1605
[0477] The system of embodiment 1603, wherein the media device, the
processor, the receiver, and the heart rate monitoring device are
in a common housing.
Embodiment 1606
[0478] The system of any one of embodiments 1601-1605, wherein the
heart rate monitoring device is in contact with the subject.
Embodiment 1607
[0479] The system of any one of embodiments 1601-1606, wherein the
advertisement electronic communication is a clinical trial
enrollment opportunity advertisement associated with the heart rate
detected in the subject.
Embodiment 1701
[0480] A method comprising presenting to a subject by a media
device an advertisement electronic communication that provides an
advertisement based on a heart rate detected in the subject by a
heart rate monitoring device, wherein the subject is performing an
exercise in a zone from 40% to 100% of a maximum heart rate in the
subject.
Embodiment 1702
[0481] The method of embodiment 1701, further comprising detecting
by the heart rate monitoring device the heart rate in the subject,
wherein the heart rate monitoring device is in contact with the
subject.
Embodiment 1703
[0482] The method of embodiment 1701 or 1702, wherein the detecting
of the heart rate in the subject is during a state of physical
exercise.
Embodiment 1704
[0483] The method of any one of embodiments 1701-1703, further
comprising receiving by a receiver from the heart rate monitoring
device a reading of the heart rate detected in the subject, wherein
the receiver is in communication with the media device.
Embodiment 1705
[0484] The method of embodiment 1704, further comprising
transmitting by the heart rate monitoring device the reading of the
heart rate detected in the subject to the receiver.
Embodiment 1706
[0485] The method of any one of embodiments 1701-1705, further
comprising presenting, contemporaneously with presenting the
instructional exercise electronic communication, by the media
device to the subject an indication of a change in the heart rate
detected in the subject in real-time by the heart rate monitoring
device.
Embodiment 1707
[0486] The method of any one of embodiments 1701-1706, wherein the
subject is diabetic.
Embodiment 1801
[0487] A computer program product comprising a non-transitory
computer-readable medium having computer-executable code encoded
therein, the computer-executable code adapted to be executed to
implement a method of advertising to a subject, the method
comprising: a) processing an advertisement system, wherein the
advertisement system comprises: i) a biometric data receiving
module; ii) an advertisement communication module; and iii) an
output module; b) receiving by the biometric data receiving module
a reading of a heart rate detected in the subject by a heart rate
monitoring device and determining that the heart rate detected in
the subject is from 40% to 100% of a maximum heart rate in the
subject; c) generating by the advertisement communication module an
advertisement based on the reading of the heart rate detected in
the subject; and d) communicating by the output module the
advertisement to an output media device.
Embodiment 1802
[0488] The computer program product of embodiment 1801, wherein the
advertisement system further comprises an instructional exercise
communication module, and the method further comprises generating
by the instructional exercise communication module an instructional
exercise communication based on the reading of the heart rate
detected in the subject.
Embodiment 1803
[0489] The computer program product of embodiment 1801 or 1802,
wherein the method further comprises communicating by the output
module the instructional exercise communication to the output media
device.
Embodiment 1804
[0490] The computer program product of embodiment 1803, wherein the
communicating of the advertisement to the output media device is
contemporaneous with the communicating of the instructional
exercise electronic communication to the output media device.
Embodiment 1805
[0491] The computer program product of any one of embodiments
1801-1804, wherein the advertisement system further comprises a
heart rate detecting module, and the method further comprises
detecting by the heart rate detecting module the heart rate in the
subject.
Embodiment 1901
[0492] A method comprising: a) reviewing by a user from a media
device an instructional exercise electronic communication; b)
performing by the user an exercise suggested by the instructional
exercise electronic communication; and c) receiving by the user
from the media device an advertisement electronic communication
that provides an advertisement upon determination that a heart rate
in the user detected by a heart rate monitoring device is in a zone
from 40% to 100% of a maximum heart rate in the user.
Embodiment 1902
[0493] The method of embodiment 1901, further comprising selecting
by the user on the media device the received advertisement
electronic communication.
Embodiment 1903
[0494] The method of embodiment 1901 or 1902, further comprising
purchasing by the user a product or a service described in the
received advertisement.
Embodiment 1904
[0495] The method of any one of embodiments 1901-1903, wherein the
advertisement electronic communication is provided during the
performing of the exercise by the user.
Embodiment 1905
[0496] The method of any one of embodiments 1901-1903, wherein the
advertisement electronic communication is provided before the
performing of the exercise by the user.
Embodiment 1906
[0497] The method of any one of embodiments 1901-1903, wherein the
advertisement electronic communication is provided after the
performing of the exercise by the user.
Embodiment 1907
[0498] The method of any one of embodiments 1901-1906, wherein the
subject is diabetic.
Embodiment 2001
[0499] A system comprising: a media device configured to present:
a) an instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) a clinical trial electronic communication based on the
biometric measurement detected in the subject.
Embodiment 2002
[0500] The system of embodiment 2001, further comprising a
processor configured to determine eligibility of the subject in a
clinical trial based on the biometric measurement detected in the
subject, wherein the processor is in communication with the media
device.
Embodiment 2003
[0501] The system of embodiment 2002, further comprising a receiver
configured to receive the biometric measurement detected in a
subject, wherein the receiver is in communication with the media
device.
Embodiment 2004
[0502] The system of embodiment 2003, wherein the media device, the
processor, and the receiver are in a common housing.
Embodiment 2005
[0503] The system of embodiment 2003, wherein the media device, the
processor, the receiver, and the biometric device are in a common
housing.
Embodiment 2006
[0504] The system of any one of embodiments 2001-2005, wherein the
biometric device is: a) in contact with the subject; b) in
communication with the media device; c) configured to detect the
biometric measurement in the subject; and d) configured to transmit
to the media device a reading of the biometric measurement detected
in the subject.
Embodiment 2007
[0505] The system of any one of embodiments 2001-2006, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 2008
[0506] The system of any one of embodiments 2001-2006, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 2101
[0507] A method comprising: a) presenting by a media device to a
subject an instructional exercise electronic communication based on
a biometric measurement detected in the subject by a biometric
device; and b) determining eligibility of the subject in a clinical
trial based on the biometric measurement detected in the
subject.
Embodiment 2102
[0508] The method of embodiment 2101, further comprising detecting
by the biometric device the biometric measurement in the subject,
wherein the biometric device is in contact with the subject.
Embodiment 2103
[0509] The method of embodiment 2102, wherein the detecting of the
biometric measurement in the subject is during a state of physical
exercise.
Embodiment 2104
[0510] The method of any one of embodiments 2101-2103, further
comprising receiving by a receiver from the biometric device a
reading of the biometric measurement detected in the subject,
wherein the receiver is in communication with the media device.
Embodiment 2105
[0511] The method of embodiment 2104, further comprising
transmitting by the biometric device the reading of the biometric
measurement detected in the subject to the receiver.
Embodiment 2106
[0512] The method of any one of embodiments 2101-2105, further
comprising presenting, contemporaneously with presenting the
instructional exercise electronic communication, by the media
device to the subject an indication of a change in the biometric
measurement detected in the subject in real-time by the biometric
device.
Embodiment 2107
[0513] The method of any one of embodiments 2101-2106, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 2108
[0514] The method of any one of embodiments 2101-2106, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 2109
[0515] The method of any one of embodiments 2101-2108, wherein the
subject is diabetic.
Embodiment 2201
[0516] A computer program product comprising a non-transitory
computer-readable medium having computer-executable code encoded
therein, the computer-executable code adapted to be executed to
implement a method of recruiting a subject in a clinical trial, the
method comprising: a) processing a clinical trial recruitment
system, wherein the clinical trial recruitment system comprises: i)
an instructional exercise communication module; ii) an clinical
trial communication module; and iii) an output module; b)
generating by the instructional exercise communication module an
instructional exercise communication based on a reading of a
biometric measurement detected in the subject by a biometric
device; c) generating by the clinical trial communication module a
clinical trial electronic communication based on the reading of the
biometric measurement in the subject; d) communicating by the
output module the instructional exercise communication to an output
media device; and e) communicating by the output module the
clinical trial electronic communication to the output media
device.
Embodiment 2202
[0517] The computer program product of embodiment 2201, wherein the
clinical trial recruitment system further comprises a biometric
data receiving module, and the method further comprises receiving
by the biometric data receiving module the reading of the biometric
measurement in the subject.
Embodiment 2203
[0518] The computer program product of embodiment 2201 or 2202,
wherein the clinical trial recruitment system further comprises a
biometric detecting module, and the method further comprises
detecting by the biometric detecting module the biometric
measurement in the subject.
Embodiment 2204
[0519] The computer program product of any one of embodiments
2201-2203, wherein the communicating of the clinical trial
electronic communication to the output media device is
contemporaneous with the communicating of the instructional
exercise electronic communication to the output media device.
Embodiment 2301
[0520] A method comprising: a) receiving by the user from a media
device an instructional exercise electronic communication; b)
performing by the user an exercise provided by the instructional
exercise electronic communication; and c) receiving by the user
from the media device a clinical trial communication that provides
a notification of a clinical trial based on a biometric measurement
in the user by a biometric device.
Embodiment 2302
[0521] The method of embodiment 2301, wherein the biometric device
is a glucose monitoring device and the biometric measurement
detected in the user is a blood glucose level.
Embodiment 2303
[0522] The method of embodiment 2301, wherein the biometric device
is a heart rate monitoring device and the biometric measurement
detected in the user is a heart rate.
Embodiment 2304
[0523] The method of embodiment 2303, wherein the clinical trial
communication is received when the heart rate detected in the user
is determined to be in a zone from 40% to 100% of a maximum heart
rate in the user.
Embodiment 2305
[0524] The method of any one of embodiments 2301-2304, further
comprising selecting by the user the received notification of the
clinical trial.
Embodiment 2306
[0525] The method of any one of embodiments 2301-2305, wherein the
clinical trial communication is provided during the performing of
the exercise by the user.
Embodiment 2307
[0526] The method of any one of embodiments 2301-2305, wherein the
clinical trial communication is provided before the performing of
the exercise by the user.
Embodiment 2308
[0527] The method of any one of embodiments 2301-2305, wherein the
clinical trial communication is provided after the performing of
the exercise by the user.
Embodiment 2309
[0528] The method of any one of embodiments 2301-2308, wherein the
user is diabetic.
Embodiment 2401
[0529] A system comprising: a media device configured to present:
a) an instructional exercise electronic communication based on a
biometric measurement detected in a subject by a biometric device;
and b) a non-exercise health recommendation to the subject based on
the biometric measurement detected in the subject.
Embodiment 2402
[0530] The system of embodiment 2401, further comprising a
processor configured to generate the non-exercise health
recommendation based on the biometric measurement detected in the
subject, wherein the processor is in communication with the media
device.
Embodiment 2403
[0531] The system of embodiment 2402, further comprising a receiver
configured to receive the biometric measurement detected in the
subject, wherein the receiver is in communication with the media
device.
Embodiment 2404
[0532] The system of embodiment 2403, wherein the media device, the
processor, and the receiver are in a common housing.
Embodiment 2405
[0533] The system of embodiment 2403, wherein the media device, the
processor, the receiver, and the biometric device are in a common
housing.
Embodiment 2406
[0534] The system of any one of embodiments 2401-2405, wherein the
biometric device is: a) in contact with the subject; b) in
communication with the media device; c) configured to detect the
biometric measurement in the subject; and d) configured to transmit
to the media device a reading of the biometric measurement detected
in the subject.
Embodiment 2407
[0535] The system of any one of embodiments 2401-2406, wherein the
biometric device is a glucose monitoring device and the biometric
measurement detected in the subject is a blood glucose level.
Embodiment 2408
[0536] The system of any one of embodiments 2401-2406, wherein the
biometric device is a heart rate monitoring device and the
biometric measurement detected in the subject is a heart rate.
Embodiment 2501
[0537] A method comprising: a) receiving by a user from a media
device an instructional exercise electronic communication; b)
performing by the user an exercise provided by the instructional
exercise electronic communication; and c) receiving by the user
from the media device a non-exercise health recommendation based on
a biometric measurement detected in the user by a biometric
device.
Embodiment 2502
[0538] The method of embodiment 2501, wherein the non-exercise
health recommendation is received when the biometric measurement
detected in the user is determined to be unsafe.
Embodiment 2503
[0539] The method of embodiment 2501 or 2502, wherein the biometric
device is a glucose monitoring device and the biometric measurement
detected in the user is a blood glucose level.
Embodiment 2504
[0540] The method of embodiment 2501 or 2502, wherein the biometric
device is a heart rate monitoring device and the biometric
measurement detected in the user is a heart rate.
Embodiment 2505
[0541] The method of embodiment 2504, wherein the non-exercise
health recommendation is received when the heart rate detected in
the user is determined to be in a zone from 40% to 100% of a
maximum heart rate in the user.
Embodiment 2506
[0542] The method of any one of embodiments 2501-2504, wherein the
non-exercise health recommendation is received during the
performing of the exercise by the user.
Embodiment 2507
[0543] The method of any one of embodiments 2501-2504, wherein the
non-exercise health recommendation is received before the
performing of the exercise by the user.
Embodiment 2508
[0544] The method of any one of embodiments 2501-2504, wherein the
non-exercise health recommendation is received after the performing
of the exercise by the user.
Embodiment 2509
[0545] The method of any one of embodiments 2501-2504, wherein the
user is diabetic.
* * * * *