U.S. patent application number 14/254684 was filed with the patent office on 2014-10-16 for discretionary insulin delivery systems and methods.
The applicant listed for this patent is Bryan MAZLISH. Invention is credited to Bryan MAZLISH.
Application Number | 20140309615 14/254684 |
Document ID | / |
Family ID | 50792568 |
Filed Date | 2014-10-16 |
United States Patent
Application |
20140309615 |
Kind Code |
A1 |
MAZLISH; Bryan |
October 16, 2014 |
DISCRETIONARY INSULIN DELIVERY SYSTEMS AND METHODS
Abstract
A method of facilitating delivery of a discretionary dose of
insulin to a user includes: enabling the user or a caregiver to
specify, via a computer-based user interface, parameters associated
with a discretionary delivery of insulin that may be delivered to
the user; subsequently receiving data that represents the user's
glucose level during a period of time associated with the
discretionary delivery; automatically determining, with a
computer-based processor, based on the received data, if, when and
how much discretionary insulin should be delivered to the user
during the period of time associated with the discretionary
delivery; delivering insulin to the user during the period of time
associated with the discretionary delivery according to the
automatic determination; and delivering insulin to the user with
the insulin delivery device according to a non-discretionary
insulin delivery schedule unless a discretionary insulin delivery
mode has been triggered.
Inventors: |
MAZLISH; Bryan; (New York,
NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MAZLISH; Bryan |
New York |
NY |
US |
|
|
Family ID: |
50792568 |
Appl. No.: |
14/254684 |
Filed: |
April 16, 2014 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61812452 |
Apr 16, 2013 |
|
|
|
61908981 |
Nov 26, 2013 |
|
|
|
Current U.S.
Class: |
604/504 ;
604/66 |
Current CPC
Class: |
A61M 5/14244 20130101;
A61B 5/4839 20130101; A61M 2205/3584 20130101; A61M 2205/3553
20130101; A61M 2230/201 20130101; G16H 20/17 20180101; A61B 5/14532
20130101; A61M 2005/14208 20130101; A61M 2205/18 20130101; A61M
2205/3561 20130101; A61M 2209/01 20130101; A61M 5/1723 20130101;
A61M 2205/3592 20130101 |
Class at
Publication: |
604/504 ;
604/66 |
International
Class: |
A61M 5/172 20060101
A61M005/172; A61M 5/142 20060101 A61M005/142 |
Claims
1. A system comprising: an insulin delivery device configured to
deliver insulin to a user of the system; a glucose monitor; and a
computer-based control unit having a user interface and a
computer-based processor, wherein the user interface enables a
caregiver to specify parameters associated with a discretionary
delivery of insulin that may be delivered to the user, wherein the
glucose monitor subsequently monitors a glucose level of the user
during a period of time associated with the discretionary delivery
and sends data representing the monitored glucose level to the
computer-based processor, wherein the computer-based processor
automatically determines, based on the data received from the
glucose monitor if, when and how much discretionary insulin should
be delivered to the user during the period of time associated with
the discretionary delivery, wherein the insulin delivery device
delivers insulin to the user during the period of time associated
with the discretionary delivery according to the automatic
determination, and wherein the system is configured to deliver
insulin to the user according to a non-discretionary insulin
delivery schedule unless a discretionary insulin delivery mode has
been triggered.
2. The system of claim 1, wherein the insulin delivery device, the
glucose monitor and the computer-based control unit are adapted to
communicate with each other using wireless communication
technology.
3. The system of claim 1, wherein the computer-based control unit
is physically integrated into either the insulin delivery device or
the glucose monitor.
4. The system of claim 1, wherein the discretionary insulin
delivery is in addition to or in lieu of some or all of the insulin
that would be delivered according to the non-discretionary insulin
delivery schedule.
5. The system of claim 1 wherein the insulin delivery device is
configured to provide to the computer-based processor data that
represents an amount of insulin that has been or will be delivered
to the user by the insulin delivery device, wherein automatically
determining if, when and how much discretionary insulin should be
delivered to the user during the period of time associated with the
discretionary delivery is based, at least on part, on the data that
represents an amount of insulin that has been or will be delivered
to the user.
6. The system of claim 1, wherein the parameters associated with
the discretionary delivery of insulin include an authorized maximum
amount of insulin to be delivered, wherein the authorized maximum
amount of insulin to be delivered is an authorized maximum amount
of delivery to be delivered during the period of time associated
with the discretionary delivery, and wherein how much discretionary
insulin should be delivered to the user is an amount between an
authorized minimum amount of insulin, which can be zero, and the
authorized maximum amount of insulin to be delivered.
7. The system of claim 1, wherein the parameters associated with
the discretionary delivery of insulin include an authorized maximum
rate of insulin delivery, wherein the authorized maximum rate of
insulin delivery is an authorized maximum rate of insulin delivery
during the period of time associated with the discretionary
delivery, and wherein the rate of discretionary insulin to be
delivered to the user is an amount between an authorized minimum
rate of insulin delivery, which can be zero, and the authorized
maximum rate of insulin delivery.
8. The system of claim 7, wherein the parameters associated with
the discretionary delivery of insulin include the period of time
associated with the discretionary delivery, wherein the period of
time associated with the discretionary delivery is a period of time
in which the caregiver has authorized discretionary delivery to
occur.
9. The system of claim 1, wherein the glucose monitor is a
continuous glucose monitor, a blood glucose meter, an intravenous
blood glucose measurement device, or other device adapted to
provide glucose data.
10. The system of claim 1, wherein the computer-based processor is
further configured to constrain delivery of the discretionary
insulin delivery based on one or more of the following constraints:
that a maximum rate of insulin delivery not be exceeded; that no
more than a maximum amount of insulin be delivered during a
specific window of time; that at least a minimum rate of insulin
delivery be maintained; and that at least a minimum amount of
insulin be delivered to the user during a specified period of
time.
11. The system of claim 1, wherein the automatic determination
includes making a dosing recommendation based one or more of the
following: a current glucose reading; an implied therapy using a
fitting algorithm; a target glucose reading; a target range of
acceptable glucose readings; an insulin-on-board level; a
carbohydrate-on-board level; and a future predicted glucose
reading.
12. The system of claim 1, wherein the computer-based processor is
configured to constrain the delivery of discretionary insulin to
the user, even if the automatic determination reveals that some
amount of discretionary insulin should be delivered to the user, if
one or more criteria have been satisfied.
13. The system of claim 12, wherein the one or more criteria
include one or more of: if IOB-(current bg-target
bg)/(C.sub.--1*ISF)-C.sub.--2>0, or if more than a fixed amount
of insulin has been delivered in a previous certain amount of time,
wherein IOB represents insulin-on-board, current bg represents a
current glucose reading, target bg represents a target glucose
reading, ISF represents an insulin sensitivity factor for the user,
and C.sub.--1 and C.sub.--2 are constants.
14. The system of claim 1, wherein the computer-based processor is
configured to: ascertain whether a cumulative amount of
discretionary insulin delivered during a specific time period has
exceeded a first threshold amount or is less than a second
threshold amount; and cease the discretionary delivery of insulin
if the cumulative amount of discretionary insulin delivered during
the specific time period has exceeded the first threshold amount or
is less than the second threshold amount.
15. The system of claim 14, further comprising: triggering an alarm
if the delivery of discretionary insulin has been suspended because
the cumulative amount of insulin delivered during the specific time
period exceeded the first threshold amount.
16. The system of claim 15, wherein the computer-based user
interface is configured to enable the user to acknowledge the
alarm; wherein the processor is configured such that: if the alarm
is acknowledged within a predetermined amount of time after the
alarm is triggered, the processor causes subsequent delivery of
insulin to the user to occur according to a non-discretionary
schedule of delivery; and if the alarm is not acknowledged within
the predetermined amount of time after the alarm is triggered, the
processor causes subsequent delivery of less insulin than would be
delivered according to the non-discretionary schedule of
delivery.
17. The system of claim 16, further comprising: wherein the
processor is configured such that, after the delivery of less
insulin than would be delivered according to the non-discretionary
insulin delivery schedule, the processor causes a subsequent
delivery of insulin according to the non-discretionary delivery
schedule.
18. The system of claim 14, wherein the first threshold amount is a
first predetermined amount of insulin above what would have been
delivered to the user according to a non-discretionary delivery
schedule over the specific time period, and wherein the second
threshold amount is a second predetermined amount of insulin less
than what would have been delivered to the user according to the
non-discretionary delivery schedule over the specific time
period.
19. The system of claim 14, further comprising: repeating the
ascertaining step on an iterative basis, wherein the specific time
period for each iteration is a period of time relative to when the
specific iteration is occurring.
20. The system of claim 19, wherein the processor is configured
such that, if the discretionary delivery is ceased, all iterations
are terminated.
21. The system of claim 1, wherein the user interface includes one
or more: keyboard, touch screen, mouse, tracking device, microphone
or other data input and/or output device or any combination
thereof.
22. A non-transitory, computer-readable medium that stores
instructions executable by a computer-based processor to perform
the steps comprising: enabling a caregiver to specify parameters at
a computer-based user interface, wherein the specified parameters
are associated with a discretionary delivery of insulin that may be
delivered to a user; subsequently receiving data that represents
the user's glucose level during a period of time associated with
the discretionary delivery; and automatically determining, based on
the received data, if, when and how much discretionary insulin, up
to a maximum amount that corresponds with the specified parameters,
should be delivered to the user during the period of time
associated with the discretionary delivery; and causing a delivery
of insulin to the user during the period of time associated with
the discretionary delivery according to the automatic
determination.
23. A method of facilitating delivery of insulin to a user, the
method including: enabling a caregiver to specify, via a
computer-based user interface, parameters associated with a
discretionary delivery of insulin that may be delivered to a user;
subsequently receiving data that represents a glucose level of the
user during a period of time associated with the discretionary
delivery; automatically determining, with a computer-based
processor, based on the received data, if, when and how much
discretionary insulin should be delivered to the user during the
period of time associated with the discretionary delivery;
delivering insulin to the user with an insulin delivery device
during the period of time associated with the discretionary
delivery according to the automatic determination; and delivering
insulin to the user with the insulin delivery device according to a
non-discretionary insulin delivery schedule unless a discretionary
insulin delivery mode has been triggered.
24. The method of claim 23, wherein the discretionary insulin
delivery is in addition to or in lieu of some or all of the insulin
that would be delivered according to the non-discretionary insulin
delivery schedule.
25. The method of claim 23, further comprising: receiving data at
the computer-based processor that represents an amount of insulin
that has been or will be delivered to the user by the insulin
delivery device over time, wherein automatically determining if,
when and how much discretionary insulin should be delivered to the
user during the period of time associated with the discretionary
delivery is based, at least in part, on the data that represents
the amount of insulin that has been or will be delivered to the
user over time.
26. The method of claim 23, wherein the parameters associated with
the discretionary delivery of insulin include an authorized maximum
amount of insulin to be delivered.
27. The method of claim 26, wherein the authorized maximum amount
of insulin to be delivered is an authorized maximum amount of
delivery to be delivered during the period of time associated with
the discretionary delivery.
28. The method of claim 26, wherein how much discretionary insulin
should be delivered to the user is an amount between an authorized
minimum amount of insulin, which can be zero, and the authorized
maximum amount of insulin to be delivered.
29. The method of claim 23, wherein the parameters associated with
the discretionary delivery of insulin include an authorized maximum
rate of insulin delivery.
30. The method of claim 29, wherein the authorized maximum rate of
insulin delivery is an authorized maximum rate of insulin delivery
during the period of time associated with the discretionary
delivery.
31. The method of claim 29, wherein the rate of discretionary
insulin to be delivered to the user is an amount between an
authorized minimum rate of insulin delivery, which can be zero, and
the authorized maximum rate of insulin delivery.
32. The method of claim 23, wherein the parameters associated with
the discretionary delivery of insulin include the period of time
associated with the discretionary delivery, wherein the period of
time associated with the discretionary delivery is a period of time
that the caregiver has authorized discretionary delivery to
occur.
33. The method of claim 23, wherein the data that represents the
user's glucose is received from a continuous glucose monitor, a
blood glucose meter, an intravenous blood glucose measurement
device, or other device adapted to provide glucose data.
34. The method of claim 23, further comprising: constraining
delivery of the discretionary insulin delivery based on one or more
of the following constraints: that a maximum rate of insulin
delivery not be exceeded; that no more than a maximum amount of
insulin be delivered during a specific window of time; that at
least a minimum rate of insulin delivery be maintained; and that at
least a minimum amount of insulin be delivered to the user during a
specified period of time.
35. The method of claim 23, wherein the automatic determination
includes making a dosing recommendation based one or more of the
following: a current glucose reading; an implied therapy using a
fitting algorithm; a target glucose reading; a target range of
acceptable glucose readings; an insulin-on-board level; a
carbohydrate-on-board level; and a future predicted glucose
reading.
36. The method of claim 35, wherein making the dosing
recommendation based upon the current glucose reading, the target
glucose reading and the insulin-on-board level comprises utilizing
the following relationship: dose.sub.--t=Max(0,
((BG_cur-BG.sub.-target)/(C.sub.--1*ISF))-(C.sub.--2*IOB)+C.sub.--3),
wherein dose_t represents a recommended dosing at time t, BG_cur
represents the current glucose reading, BG_target represents the
target glucose reading, ISF represents an insulin sensitivity
factor for the user, and C.sub.--1, C.sub.--2 and C.sub.--3 are
constants.
37. The method of claim 35, wherein making the dosing
recommendation based on the implied therapy using the fitting
algorithm comprises utilizing the following relationship:
dose.sub.--t=Max(0,
(C.sub.--1*(BGcur-BGtarg)/ISF)+(C.sub.--2*COB/carb
ratio)-(C.sub.--3*IOB)+C.sub.--4), wherein dose_t represents a
recommended dosing at time t, BG_cur represents the current glucose
reading, BG_target represents the target glucose reading, ISF
represents an insulin sensitivity factor for the user, COB
represents carbohydrates-on-board for the user, carb ratio
represents a number of carbohydrates that one unit of insulin
offsets for the user, IOB represents insulin-on-board for the user,
and C.sub.--1, C.sub.--2, C.sub.--3 and C.sub.--4 are
constants.
38. The method of claim 35, further comprising: calculating the
future predicted glucose reading utilizing a
proportional-derivative extrapolation of the future predicted
glucose reading from the current glucose reading and a recent trend
in glucose readings.
39. The method of claim 35, further comprising: calculating the
future predicted glucose reading utilizing one or more of the
following: a proportional, plus integral, plus derivative
extrapolation of the future predicted glucose reading from the
current glucose reading and a recent trend in glucose readings; an
autoregressive model; and a compartmental model of glucose and
insulin transport.
40. The method of claim 35, wherein making the dosing
recommendation based on the target range of BG levels comprises
determining, with the computer-based processor, an error associated
with the projected future glucose reading relative to the target
range of acceptable glucose readings, wherein: the error is a
function of the projected future glucose reading and an upper value
in the target range of acceptable glucose readings that increases
as the absolute difference between the two values increases, if the
projected future glucose reading is greater than the upper value;
the error is a function of the projected future glucose reading and
a lowest value in the target range of acceptable glucose readings
that decreases as the absolute difference between the two values
increases, if the projected future glucose reading is less than the
lowest value; and the error is zero if the projected future glucose
reading is equal to the lowest value or the upper value or is
between the lowest value and the upper value.
41. The method of claim 23, further comprising: constraining the
delivery of discretionary insulin to the user, even if the
automatic determination reveals that some amount of discretionary
insulin should be delivered to the user, if one or more criteria
have been satisfied.
42. The method of claim 41, wherein the one or more criteria
include one or more of: if IOB-(current bg-target
bg)/(C.sub.--1*ISF)-C.sub.--2>0, or if more than a fixed amount
of insulin has been delivered in a previous certain amount of time,
wherein IOB represents insulin-on-board, current bg represents a
current glucose reading, target bg represents a target glucose
reading, ISF represents an insulin sensitivity factor for the user,
and C.sub.--1 and C.sub.--2 are constants.
43. The method of claim 23, further comprising: ascertaining
whether a cumulative amount of discretionary insulin delivered
during a specific time period has exceeded a first threshold amount
or is less than a second threshold amount; and ceasing the
discretionary delivery of insulin if the cumulative amount of
discretionary insulin delivered during the specific time period has
exceeded the first threshold amount or is less than the second
threshold amount.
44. The method of claim 43, further comprising: triggering an alarm
if the delivery of discretionary insulin has been suspended because
the cumulative amount of insulin delivered during the specific time
period exceeded the first threshold amount.
45. The method of claim 44, further comprising: enabling the user
to acknowledge the alarm; if the alarm is acknowledged within a
predetermined amount of time after the alarm is triggered,
subsequently delivering insulin to the user according to a
non-discretionary insulin delivery schedule; and if the alarm is
not acknowledged within the predetermined amount of time after the
alarm is triggered, subsequently delivering less insulin than would
be delivered according to the non-discretionary insulin delivery
schedule.
46. The method of claim 45, further comprising: after delivering
less insulin than would be delivered according to the
non-discretionary insulin delivery schedule, delivering insulin
according to the non-discretionary delivery schedule.
47. The method of claim 46, wherein subsequently delivering less
insulin than otherwise would be delivered according to the
non-discretionary insulin delivery schedule at least partially
offsets additional insulin that the user may have received as a
result of the discretionary delivery.
48. The method of claim 46, wherein subsequently delivering less
insulin than would be delivered according to the non-discretionary
insulin delivery schedule comprises: delivering an amount of
insulin that is between 0 and a multiple of the first threshold
amount less than what would be delivered according to the
non-discretionary schedule of delivery from a beginning of the
discretionary insulin delivery period until a termination of the
discretionary insulin delivery period.
49. The method of claim 43, wherein the first threshold amount is a
first predetermined amount of insulin above what would have been
delivered to the user according to a non-discretionary delivery
schedule over the specific time period, and wherein the second
threshold amount is a second predetermined amount of insulin less
than what would have been delivered to the user according to the
non-discretionary delivery schedule over the specific time
period.
50. The method of claim 43, further comprising: repeating the
ascertaining step on an iterative basis, wherein the specific time
period for each iteration is a period of time relative to when the
specific iteration is occurring.
51. The method of claim 50, wherein all iterations are terminated
upon the occurrence of a ceasing of discretionary delivery.
52. A control system configured to control an amount of insulin
delivered to a user, the control system comprising: a
computer-based control unit having a user interface and a
computer-based processor; a first interface unit configured to
allow the computer-based processor to communicate with a glucose
monitor; and a second interface unit configured to allow the
computer-based processor to communicate with an insulin delivery
device which is configured to deliver insulin to a user of the
system, wherein the user interface enables a caregiver to specify
parameters associated with a discretionary delivery of insulin that
may be delivered to the user, wherein the computer-based processor
is configured to subsequently receive data from a glucose monitor
through the first interface unit, wherein the received data
represents a glucose level of the user during a period of time
associated with the discretionary delivery, wherein the
computer-based processor is configured to automatically determine,
based on the data received from the glucose monitor if, when and
how much discretionary insulin should be delivered to the user
during the period of time associated with the discretionary
delivery, wherein the computer-based processor is configured to
send data to an insulin delivery device through the second
interface unit such that the insulin delivery device can deliver
insulin to the user during the period of time associated with the
discretionary delivery according to the automatic determination,
and wherein the computer-based processor is configured to send data
to an insulin delivery device through the second interface unit
such that the insulin delivery device can deliver insulin to the
user according to a non-discretionary insulin delivery schedule
unless a discretionary insulin mode has been triggered.
53. The control system of claim 52, wherein the first interface
unit comprises a wireless receiver or transceiver, and the second
interface unit comprises a wireless transmitter or transceiver.
54. The control system of claim 52, wherein the computer-based
processor is configured to send data to an insulin delivery device
to deliver insulin to the user without the use of data received
from a glucose monitor in providing a predetermined,
non-discretionary insulin delivery schedule to the insulin delivery
device.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit under 35 U.S.C. 119 of
U.S. Provisional Application No. 61/812,452 filed Apr. 16, 2013 and
entitled "Discretionary Insulin Delivery", and of U.S. Provisional
Application No. 61/908,981 filed Nov. 26, 2013 and entitled
"Discretionary Insulin Delivery".
INCORPORATION BY REFERENCE
[0002] All publications and patent applications mentioned in this
specification are herein incorporated by reference to the same
extent as if each individual publication or patent application was
specifically and individually indicated to be incorporated by
reference.
FIELD
[0003] This disclosure relates to the discretionary delivery of
insulin to a user (e.g., a person with diabetes) and, more
particularly, this disclosure relates to systems and methods for
delivering a discretionary dose of insulin to a user.
BACKGROUND
[0004] Diabetes mellitus is a chronic metabolic disorder caused by
an inability of a person's pancreas to produce sufficient amounts
of insulin, such that the person's metabolism is unable to provide
for the proper absorption of sugar and starch. This failure leads
to hyperglycemia, i.e. the presence of an excessive amount of
analyte within the blood plasma. Persistent hyperglycemia has been
associated with a variety of serious symptoms and life threatening
long term complications such as dehydration, ketoacidosis, diabetic
coma, cardiovascular diseases, chronic renal failure, retinal
damage and nerve damages with the risk of amputation of
extremities. Because healing is not yet possible, a permanent
therapy is necessary which provides constant glycemic control in
order to constantly maintain the level of blood analyte within
normal limits. Such glycemic control is achieved by regularly
supplying external drugs to the body of the patient to thereby
reduce the elevated levels of blood analyte.
[0005] An external biologically effective drug (e.g., insulin or
its analog) was commonly administered by means of multiple, daily
injections of a mixture of rapid and intermediate acting drug via a
hypodermic syringe. While this treatment does not require the
frequent estimation of blood analyte, it has been found that the
degree of glycemic control achievable in this way is suboptimal
because the delivery is unlike physiological drug production,
according to which drug(s) enters the bloodstream at a lower rate
and over a more extended period of time.
[0006] Improved glycemic control may be achieved by the so-called
intensive drug therapy which is based on multiple daily injections,
including one or two injections per day of a long acting drug for
providing basal drug and additional injections of a rapidly acting
drug before each meal in an amount proportional to the size of the
meal. Although traditional syringes have at least partly been
replaced by drug pens, the frequent injections are nevertheless
very inconvenient for the patient, particularly those who are
incapable of reliably self-administering injections.
[0007] Substantial improvements in diabetes therapy have been
achieved by the development of other drug delivery devices, such as
insulin pumps, relieving the patient of the need for syringes or
drug pens and the administration of multiple, daily injections.
Insulin pumps allow for the delivery of insulin in a manner that
bears greater similarity to the naturally occurring physiological
processes and can be controlled to follow standard or individually
modified protocols to give the patient better glycemic control.
[0008] In addition, delivery directly into the intraperitoneal
space or intravenously can be achieved by drug delivery devices.
Drug delivery devices can be constructed as an implantable device
for subcutaneous arrangement or can be constructed as an external
device with an infusion set for subcutaneous infusion to the
patient via the transcutaneous insertion of a catheter, cannula or
a transdermal drug transport such as through a patch. External drug
delivery devices are mounted on clothing, hidden beneath or inside
clothing, or mounted on the body and are generally controlled via a
user interface built-in to the device or on a separate remote
device.
[0009] Drug delivery devices have been utilized to assist in the
management of diabetes by infusing drug or a suitable biologically
effective material into the diabetic patient at a basal rate with
additional drug or "bolus" to account for meals or high analyte
values, levels or concentrations. The drug delivery device
typically is connected to an infuser, better known as an infusion
set by a flexible hose. The infuser typically has a subcutaneous
cannula, and an adhesive backed mount on which the cannula is
attached. The cannula may include a quick disconnect to allow the
cannula and mount to remain in place on the skin surface of the
user while the flexible tubing is disconnected from the infuser.
Regardless of the type of drug delivery device, blood analyte
monitoring is typically required to achieve acceptable glycemic
control. For example, delivery of suitable amounts of drug by the
drug delivery device requires that the patient frequently determine
his or her blood analyte level and manually input this value into a
user interface for the external drug delivery device, which then
may calculate a suitable modification to the default or currently
in-use drug delivery protocol, i.e. dosage and timing, and
subsequently communicates with the drug delivery device to adjust
its operation accordingly. The determination of blood analyte
concentration is typically performed by means of an episodic
measuring device such as a hand-held electronic meter which
receives blood samples via enzyme-based test strips and calculates
the blood analyte value based on the enzymatic reaction. In recent
years, continuous analyte monitoring has also been utilized with
drug delivery devices to allow for greater control of the drug(s)
being infused into the diabetic patients.
[0010] People with diabetes should maintain tight control over
their lifestyle, so that they are not adversely affected by, for
example, irregular food consumption, exercise or stress. In
addition, a physician dealing with a particular individual with
diabetes may require detailed information on the individual's
lifestyle to provide effective treatment or modification of
treatment for controlling diabetes. Currently, one of the ways of
monitoring the lifestyle of an individual with diabetes has been
for the individual to keep a paper logbook of their lifestyle.
Another way is for an individual to simply rely on remembering
facts about their lifestyle and then relay these details to their
physician on each visit.
[0011] The aforementioned methods of recording lifestyle
information are inherently difficult, time consuming, and often
inaccurate. Paper logbooks are not necessarily always carried by an
individual and may not be accurately completed when required. Such
paper logbooks are small and it is therefore difficult to enter
detailed information requiring detailed descriptors of lifestyle
events. Furthermore, an individual may often forget key facts about
their lifestyle when questioned by a physician who has to manually
review and interpret information from a hand-written notebook.
There is no analysis provided by the paper logbook to distill or
separate the component information. Also, there are no graphical
reductions or summary of the information. Entry of data into a
secondary data storage system, such as a database or other
electronic system, requires a laborious transcription of
information, including lifestyle data, into this secondary data
storage. Difficulty of data recordation encourages retrospective
entry of pertinent information that results in inaccurate and
incomplete records.
[0012] In light of the many deficiencies and problems associated
with current systems and methods for maintaining proper glycemic
control, enormous resources have been put into finding better
solutions. It has been contemplated for many years that it should
be entirely feasible to couple a continuous glucose monitoring
system with an insulin delivery device to provide an "artificial
pancreas" to assist people living with diabetes. However,
developing such workable solutions to the problem that are simple,
safe, reliable and able to gain regulatory approval has proved to
be elusive. What has been needed and has not been provided by the
prior art is a system and method that provide a level of automatic
control of insulin delivery devices for improved insulin delivery
and glycemic control that is simple, safe, and reliable in a real
world setting.
SUMMARY OF THE DISCLOSURE
[0013] In one aspect, a method of facilitating delivery of a
discretionary dose of insulin to a user includes: enabling the
person to specify parameters associated with a discretionary
delivery of insulin that may be delivered to the user; subsequently
receiving data that represents the user's glucose level during a
period of time associated with the discretionary delivery;
automatically determining, based on the received data, if, when and
how much discretionary insulin should be delivered to the user
during the period of time associated with the discretionary
delivery; and delivering insulin to the user during the period of
time associated with the discretionary delivery according to the
automatic determination.
[0014] Also disclosed is a computer-based system configured to
perform various implementations of the foregoing method.
[0015] In general, the period of time associated with the
discretionary delivery can be any period of time, during which the
computer-based system is authorized to deliver one or more doses of
insulin to the user at the system's discretion. This period of time
may be something that the user or a caregiver has specified in
setting up the parameters for the discretionary delivery. However,
the period of time need not be particularly specified by the user
or caregiver. The period of time may be a single discrete time
period. Alternatively, it may be one of a series of consecutive or
non-consecutive time periods. Finally, the period of time can be of
virtually any duration.
[0016] The discretionary insulin delivery can be in addition to
insulin delivered pursuant to a non-discretionary insulin delivery
schedule or in lieu of some or all of the insulin that would have
been delivered pursuant to a non-discretionary insulin delivery
schedule.
[0017] In some implementations, the method includes delivering
insulin, with an insulin delivery pump, to the user according to a
non-discretionary insulin delivery schedule unless the
computer-based processor determines that a discretionary insulin
delivery should occur. According to some implementations, the
method includes, receiving data at the computer-based processor
that represents an amount and timing of insulin that has been or
will be delivered to the user by the insulin delivery pump over
time. In those implementations, automatically determining if, when
and how much discretionary insulin should be delivered to the user
during the period of time associated with the discretionary
delivery can be based, at least in part, on the data that
represents an amount and timing of insulin that has been or will be
delivered to the user over time.
[0018] In certain implementations, delivery of a discretionary dose
of insulin may be constrained, even if the user's recent glucose
readings show an upward trend, for example. In some
implementations, the delivery of discretionary insulin to the user
constraint may be based on estimated insulin-on-board for the user.
In other implementations, discretionary delivery may be constrained
if a recent glucose reading is below or above a certain
threshold.
[0019] Some implementations include an alarm. For example, in some
implementations, the method includes triggering the alarm if the
delivery of discretionary insulin has been terminated because a
cumulative amount of discretionary insulin delivered during a
specific time period exceeded a threshold amount. Moreover,
typically, the user can acknowledge the alarm. If the alarm is
acknowledged within a predetermined amount of time after the alarm
is triggered, the method includes subsequently delivering insulin
to the user according to a non-discretionary insulin delivery
schedule. If the alarm is not acknowledged within the predetermined
amount of time after the alarm is triggered, the method includes
subsequently delivering less insulin than would be delivered
according to the non-discretionary insulin delivery schedule.
[0020] In some implementations, one or more of the following
advantages may be present.
[0021] For example, insulin can be delivered to people who need it
in closer correspondence to exactly how much insulin they need and
when they need it. Mis-estimation of insulin requirements is a
common problem for users with diabetes and allowing the automatic
determination to either reduce or increase the insulin delivery
automatically has the potential to significantly mitigate some of
the burdens of managing diabetes. Moreover, the discretion that a
system can automatically exercise in augmented delivery of insulin
is made highly safe by virtue of the alarming and automatic
correction of a possible over-delivery functionality disclosed
herein.
[0022] Other features and advantages will be apparent from other
portions of this specification, including the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0023] FIG. 1 is a schematic view of an exemplary system adapted to
implement one or more of the techniques disclosed herein.
[0024] FIG. 2 is a schematic diagram illustrating an example of the
controller in FIG. 1.
[0025] FIG. 3 is a flowchart showing one implementation of a method
that includes facilitating a discretionary delivery of insulin to a
user.
[0026] FIG. 4 is a schematic diagram of an exemplary system adapted
to facilitate the functionalities disclosed herein for a particular
user and to communication or interact with one or more pc-based web
browsers and client phones over a wireless network.
[0027] FIG. 5 is a plot of blood glucose versus
insulin-on-board.
[0028] FIG. 6 is a plot of basal rate multipliers versus blood
glucose levels.
[0029] FIG. 7 is a time plot showing blood glucose readings and a
projected blood glucose level.
[0030] FIG. 8 is an exemplary representation of the behavior of the
system in FIG. 1.
[0031] FIG. 9 is another exemplary representation of the behavior
of the system in FIG. 1.
[0032] FIG. 10 is a time plot showing a computer simulation of the
effect on glucose level after a maximum discretionary limit alarm
has been triggered but remains unacknowledged.
[0033] FIG. 11 is an exemplary representation of the behavior of
the system in FIG. 1.
[0034] FIG. 12 is an exemplary representation of the behavior of
the system in FIG. 1.
DETAILED DESCRIPTION
[0035] FIG. 1 is a schematic view of an exemplary system 100
adapted to implement one or more of the techniques disclosed
herein.
[0036] The illustrated system 100 includes a glucose
monitoring/measuring device 102, an insulin delivery device such as
a pump 104 and a controller 106. The controller 106 has a user
interface 108, an internal computer-based processor and internal
computer-based memory storage capacity.
[0037] In a typical implementation, the insulin pump 104 is adapted
to deliver insulin to a user (e.g., a person with diabetes)
according to a non-discretionary insulin delivery schedule. The
non-discretionary insulin delivery schedule is non-discretionary
because insulin will be delivered according to what the schedule
indicates, regardless of what the user's actual blood glucose
levels are and regardless of how much insulin already has been
delivered to the user.
[0038] As used herein, a "user" is typically a person who receives
insulin from the inventive devices, systems and methods disclosed
herein. In some implementations, actions may be performed by a
"caregiver" who is a person or persons different from the "user".
For example, the caregiver may be a parent, other family member,
teacher, physician, clinician, advisor, or other person(s)
assisting the user with management of his or her diabetes. In some
implementations, actions ascribed to a caregiver must be performed
by the caregiver(s) and may not be performed by the user. In other
implementations, the user and the caregiver are one and the same
person, and there is no other person directly involved in the
delivery of insulin to the user.
[0039] Non-discretionary insulin delivery may include a constant
infusion, basal rates; point in time bolus delivery and; fixed rate
bolus delivery over a set period of time. The various
non-discretionary insulin delivery programs may be combined by the
user in virtually any combination. This delivery is
non-discretionary in that once the user or caregiver requests the
insulin delivery; the delivery will happen regardless of the user's
blood glucose levels and regardless of how much insulin has already
been delivered to the user. In some implementations, the only way a
user's non-discretionary delivery is changed is if the user or a
caregiver takes an action to change the pre-defined delivery. Thus,
we define non-discretionary delivery in these implementations as
insulin delivery that is determined solely by the user or a
caregiver and where there is no discretion left to the insulin pump
control system as to whether to give more or less than the user or
caregiver has requested or programmed.
[0040] Additionally, in a typical implementation, the system 100 is
adapted to facilitate delivery of insulin to the user on a
discretionary basis. In this regard, the system 100 is able to
deliver insulin to the user on an "as needed" basis within
parameters defined by the user or caregiver. A discretionary
insulin delivery is a permissible but not mandatory delivery of
insulin and is automatically delivered (i.e., without further
involvement from the user or caregiver) to the user if the system
determines that such a delivery is warranted (i.e., such a delivery
would be helpful to the user) and is not otherwise constrained from
implementing the discretionary delivery.
[0041] A discretionary delivery of insulin can be in addition to
whatever insulin is being delivered according to the
non-discretionary insulin delivery schedule, or in lieu of some or
all of the insulin that would have been delivered according to the
non-discretionary insulin delivery schedule.
[0042] For example, a discretionary delivery could allow varying
the pre-programmed basal rate of z units per hour to a basal rate
between x units per hour and y units per hour. In this case, the
discretionary delivery would be in lieu of the non-discretionary
basal delivery. That is, during the time of the discretionary
delivery, the pre-programmed constant basal rate of z units per
hour would be replaced by the discretionary delivery that could
vary between x and y units per hour. The system may constantly
adjust this rate of delivery based on a variety of factors. Z would
typical be contained in the range defined by x and y but there may
be situations where it lies outside of that range.
[0043] A discretionary delivery may also be requested in addition
to a non-discretionary delivery program. For example, a system may
allow a discretionary bolus where the user defines a minimum and
maximum amount of insulin to be delivered over a certain time
period. In a situation where a user eats a meal that requires
between 3 and 6 units of insulin, this type of bolus could be very
helpful to the user. In this scenario, the user or caregiver could
program a discretionary bolus with minimum 3 units and maximum 6
units of insulin to be delivered over some amount of time
determined by the user. In this way, the user may let the system
manage the uncertainty associated with how much insulin is actually
required. In this example, the discretionary delivery is in
addition to the non-discretionary basal rate delivery previously
programmed by the user.
[0044] In this regard, the system 100 is adapted to enable the user
or caregiver to specify parameters associated with the
discretionary insulin delivery. The parameters may define one or
more time periods within which a discretionary insulin delivery may
occur. The parameters also may specify a maximum amount of insulin,
a maximum rate of insulin delivery, a minimum amount of insulin, a
minimum rate of insulin delivery, etc. for one or more (or all) of
the specified time periods. The parameters may specify whether the
discretionary delivery, if deemed warranted, should be in addition
to any insulin being delivered according to the non-discretionary
insulin delivery schedule, or in lieu of some or all of the insulin
that otherwise would have been delivered according to the
non-discretionary insulin delivery schedule.
[0045] The exemplary system 100 is also adapted to determine,
during any periods of time that a discretionary insulin delivery
may occur, whether a discretionary insulin delivery is warranted
(i.e., whether a discretionary insulin delivery would likely help
the user). In a typical implementation, this determination is made
on a rolling basis. In one implementation, for example, a new
determination is made every five minutes, based on any information
received in a four-hour time window immediately preceding the time
that the new determination is made.
[0046] The determination of whether a discretionary delivery is
warranted can be made based on various information including, for
example, the user's blood glucose level over time and an estimate
of how much insulin-on-board (IOB) is in the user's body.
[0047] In general, the user's IOB represents an amount of insulin
that has already been delivered to the user but has yet to act on
the user's blood glucose level. In a typical implementation, the
system 100 can estimate IOB for the user based on information about
recent actual insulin deliveries from the insulin pump 104 and
insulin absorption information (e.g., the user's insulin absorption
curve, the user's duration of insulin action (DIA) which defines
how long it takes for 100% absorption, etc.) that may be specific
to the user.
[0048] Traditional insulin-on-board calculations typically do not
include basal rate insulin deliveries. Such basal deliveries
typically are intended to merely maintain the current blood glucose
level, not to raise or lower it, and not to offset the effect of a
meal, etc., as does a bolus delivery. However, as used herein, the
calculation of insulin-on-board may include some or all of the
following: non-discretionary meal related bolus insulin;
non-discretionary correction related bolus insulin;
non-discretionary extended bolus delivery; non-discretionary basal
insulin delivery; and insulin delivered as part of a discretionary
delivery request.
[0049] Insulin on board for a point delivery of insulin (such as a
bolus) may be determined by multiplying the amount of the insulin
delivery by the percentage of absorption remaining as determined by
the time since the delivery, the absorption curve and the DIA. A
typical absorption curve will define a percentage of insulin
remaining on the y-axis by the time since bolus on the x-axis.
[0050] To calculate insulin on board for a continuous delivery of
insulin such as a basal delivery or an extended bolus, the
continuous delivery of insulin may be discretized into very small
bolus deliveries of insulin. For example, if a basal rate is 1 unit
per hour and we would like to calculate the insulin on board from 1
hour of such a basal rate, we could discretize the basal delivery
into 60 boluses of 1/60th of a unit, delivered at minute 1, 2, 3, .
. . , 60 of the hour. Once discretized, the IOB for each individual
discretized bolus may be calculated as described above, and then
summed together to compute the IOB for the entire continuous
delivery.
[0051] The insulin on board for a discretionary delivery that is in
addition to a non-discretionary delivery may be calculated in the
same manner as a non-discretionary delivery. That is, any point
deliveries of the discretionary delivery may be calculated as if it
were a bolus. A continuous discretionary delivery may be calculated
by following the discretization method described above.
[0052] In some implementations, it may be beneficial to calculate
the IOB of a discretionary delivery by calculating it relative to
the non-discretionary delivery that the discretionary delivery
replaced. For example, take a discretionary delivery that allows
the basal rate to vary between x and y units per hour in lieu of
the pre-programmed z units per hour. In some implementations, the
IOB for the discretionary delivery may be calculated by computing
the IOB for both the discretionary delivery (IOB_discretionary) and
for the non-discretionary delivery that it replaced
(IOB_non-discretionary) and then taking the difference,
IOB_discretionary--IOB_non-discretionary to find the IOB to assign
to the period of the discretionary delivery. Note that in cases
where the IOB_discretionary is less than the IOB_non-discretionary,
the IOB calculated for such discretionary delivery period is
negative. A negative IOB may be added to any other IOB from other
deliveries (positive or negative) in a simple additive manner to
calculate the total IOB for the user.
[0053] A negative IOB reflects that the user has received less
insulin than the pre-programmed, non-discretionary delivery would
have delivered. Since standard insulin therapy provides for the
pre-programmed basal delivery to keep glucose values at static
levels, the delivery of less than the pre-programmed basal rate
results in a deficit of insulin relative to what the user would
need to keep glucose levels static. This deficit results in an
expected subsequent rise in glucose values equal to the absolute
value of the insulin deficit amount multiplied by the user's
insulin sensitivity factor (ISF).
[0054] In some implementations, the benefit of computing the IOB of
a discretionary delivery on a relative basis is that it allows the
user or caregiver to more easily understand what the net effect is
of the therapy changes from the discretionary delivery. Depending
on the implementation, the discretionary delivery may delivery more
or less than the non-discretionary, pre-programmed delivery
schedule. The relative IOB calculation allows the user to see if
the net effect of the discretionary delivery is an increase
(positive IOB) or decrease (negative IOB) to the standard,
pre-programmed delivery schedule.
[0055] If a discretionary delivery of insulin is warranted, the
system 100 is further adapted to determine how much discretionary
insulin should be delivered and when exactly it should be
delivered. In this regard, the system 100 may be programmed with
logic to make these decisions based on a variety of information,
such as the user's current or predicted blood glucose level, IOB
level, etc. Moreover, the system may be guided in these decisions
by the parameters specified by the user in authorizing the
discretionary delivery and/or other system delivery
constraints.
[0056] In general, authorizing a discretionary insulin delivery
gives the system 100 some flexibility in administering insulin to
the user. This can be advantageous in a number of situations. For
example if the user or caregiver is unsure about what effect eating
a particular meal might have on the user's blood glucose level,
that person might authorize a discretionary insulin delivery to
give the system 100 a better chance of managing any unpredicted
swings in blood glucose.
[0057] Moreover, since the user or caregiver is able to set the
parameters associated with any discretionary delivery, there is an
inherent degree of safety built-in to the system 100. This is
because the user or caregiver would not likely specify parameters
that might result in harm. In some implementations, there is one or
more additional safety measures built into the system as well.
[0058] One of those additional safety measures, for example, may be
the system 100 having certain delivery constraints. In general, a
delivery constraint may be considered a hard limit on discretionary
insulin delivery that the system 100 cannot violate under any
circumstances. So, even if the system 100 were to determine that a
particular discretionary insulin delivery was warranted, if that
discretionary delivery would result in one or more of the delivery
constraints being violated, then the discretionary delivery would
not be delivered, or at least would be truncated so as to not
violate any delivery constraints.
[0059] Some exemplary delivery constraints include: that a
particular amount of insulin must be delivered over or within a
particular minimum or maximum length of time; that a rate of
insulin delivery must not exceed some specified maximum rate; that
an amount of insulin delivery during a particular length of time
must not exceed a specified maximum amount; that the rate of
insulin delivery at any point in time must be at least a specified
minimum; that an amount of insulin delivered during a particular
window of time must be at least a specified minimum amount,
etc.
[0060] Moreover, in situations where the system 100 is considering
whether to add insulin, the system 100 may constrain delivery of
discretionary insulin to the user, even if the system 100 otherwise
determines that some amount of discretionary insulin would be
appropriate to be delivered to the user, if one or more criteria
have been satisfied. These criteria can include, for example, if
IOB-(current bg-target bg)/(C.sub.--1*ISF)-C.sub.--2>0, or if
more than a fixed amount of insulin has been delivered in the past
N hours or minutes (or any unit of time), where IOB represents
insulin-on-board, and ISF represents an insulin sensitivity factor,
and C.sub.--1 and C.sub.--2 are constants defined by the user and
in some implementations C.sub.--2 is a function of the
preprogrammed basal rate. In some cases, C.sub.--2 may be a fixed
amount of insulin while in others it may be a function of a current
or future preprogrammed basal rate. C.sub.--2 may be either
positive or negative with a negative value creating a more
conservative dosing approach.
[0061] Other implementations may constrain the discretionary
delivery when the IOB is large when compared to the spread between
the recent bg and the target bg range. The spread between the
recent bg and the target bg may be a simple difference, a
difference of the logarithms of the two values or virtually any
function of the two values that increases as the recent bg
increases and moves away from the target range.
[0062] There may additionally be constraints for a discretionary
delivery that require that the most recent glucose level is above
(or below) a threshold in order to augment (or attenuate) the
non-discretionary delivery program it replaces.
[0063] An additional safety measure that may be included in certain
implementations is an alarm. The alarm may be incorporated into the
controller 106, for example. The alarm can be an audible, visual
and/or tactile.
[0064] The alarm can be adapted to trigger in response to various
possible conditions including, for example, when the user's blood
glucose level passes certain threshold values or when the amount of
insulin that has been delivered as part of a discretionary delivery
exceeds some threshold value. For example, the alarm might trigger
if all of the insulin that has been authorized for discretionary
delivery during a particular period of time has been delivered to
the user. If an alarm occurs, the system 100 is generally adapted
to indicate to the user and/or caregiver what condition or
conditions triggered the alarm. Moreover, the system 100 typically
is adapted to enable the user or caregiver to acknowledge a
triggered alarm.
[0065] In some implementations, if the alarm triggers because the
system 100 has delivered a prescribed maximum amount of
discretionary insulin to the user in a given time period, then the
person's acknowledgement of the alarm may be considered a
verification by the system that the person considers this maximum
delivery to be acceptable.
[0066] In some implementations, the alarm may trigger based on a
weighted sum of insulin delivered over a given time period. In this
case, a weight may be assigned to every sub-period of time, such as
every five minutes. Typically, the weights would be a function of
how long in the past from the current time the sub-period is. A
simple weighting scheme, as noted above, would involve using a
weight of 1 for all sub-periods in a given time period and 0 for
all sub-periods prior. In some implementations, a more complex
weighting scheme may include using an exponential decay function to
assign a greater weight to more recent sub-periods. Such a
weighting scheme could assign a value of e (-alpha*period) where
period is the number of sub-periods back from the current time and
alpha is some positive real number. For example, if the sub-periods
are five-minutes long, then a value for alpha of 0.03 would be a
reasonable value in some implementations. Other implementations may
use arbitrary weighting schemes that may relate to the absorption
profile of the insulin or virtually any function that seems
appropriate.
[0067] Another method for triggering an alarm would entail
independently examining the amount of dosing in each sub-period
over a given period. Each sub-period may then be assigned a certain
value based on whether insulin was augmented or attenuated during
the sub-period. This sub-period-value may be a function of how much
the insulin was increased or decreased during the sub-period or it
may be a simple 1, 0, -1 for whether the insulin was augmented,
unchanged, or attenuated, respectively. In some implementations,
the system is only interested in sub-periods when insulin is
augmented and thus could use a function that assigns a 1 to any
sub-period where insulin was increased and a 0 to all other
sub-periods. These exemplary systems represent a small fraction of
the possible sub-period-value-functions that may suit different
implementations. Once the values for each sub-period have been
determined they may be summed in a weighted fashion, as described
above, to come up with a metric on which an alarm may be based.
[0068] For example, one implementation of this type of alarm would
be for the system to terminate discretionary insulin delivery if
more than 80% of the 5 minute periods during the past 3 hours have
resulted in the a discretionary insulin delivery greater than the
non-discretionary program would have delivered. This alarm may be
independent and irrespective of whether the total amount of insulin
delivered is greater than a pre-determined maximum dosing amount.
If such an alarm goes off, then the actual amount of discretionary
insulin delivered during the given time period may be considered to
be the maximum-discretionary-amount for the purposes of subsequent
attenuation described below.
[0069] In some implementations, if the person does not acknowledge
the alarm in a timely manner (e.g., because he or she is sleeping
or otherwise unconscious), then the system 100 will automatically
reduce (i.e., without input from the person) the amount of insulin
to be delivered in a period of time following the person's failure
to acknowledge the alarm. Typically, this reduction of insulin
delivery in the period following the person's failure to
acknowledge the maximum-discretionary-delivery alarm is intended to
at least partially offset what could potentially have been an
over-dosage of insulin resulting from a discretionary delivery. In
some implementations, under these circumstances, the system 100
reduces the amount and rate of insulin delivery to zero for such
period until the difference between the amount of insulin the
non-discretionary delivery schedule would have delivered equals the
prescribed maximum discretionary amount of insulin that was
previously delivered. In other implementations, under these
circumstances, the reduction in subsequent non-discretionary
delivery would equal the difference between the prescribed maximum
discretionary delivery schedule and the non-discretionary delivery
that would have occurred during the time period of the
discretionary delivery. In these scenarios, the non-discretionary
delivery schedule would subsequently resume at the end of such
period.
[0070] Typically, the alarm functionality addresses a concern that
the continuous glucose monitor 102 readings that may help determine
discretionary insulin deliveries may be inaccurate for some period
of time resulting in a sub-optimal excessive dosing of insulin to
the user. In some implementations, the alarm functionality can
mitigate (or alleviate) some concerns and problems associated with
such occurrences. When the discretionary delivery reaches a maximum
authorized dose, for example, the person is alerted that he or she
should verify that the dosing was appropriate and, if not, take
preventive action to offset the unnecessary insulin dosing with
carbohydrates before the insulin potentially dangerously lowers
blood glucose levels. In the event that the user or caregiver is
unable to acknowledge the alert due to unconsciousness or sleep,
the system 100 automatically takes corrective action to ameliorate
potential negative effects of excessive-dosing.
[0071] In some implementations, the system 100 determines whether
to make a discretionary delivery of insulin based on information
from the continuous glucose meter 102 regarding the user's blood
glucose levels. If, for example, the information provided by the
continuous glucose meter 102 to help the system 100 make a
determination in this regard was inaccurate, then it is possible
that the user may have improperly received an excessive dose of
insulin. Under those circumstances, and if the person does not
acknowledge the resulting alarm (e.g., due to being asleep, etc.),
then the system 100 will take corrective action automatically.
[0072] In the illustrated implementation, the glucose
monitoring/measuring device 102, the insulin pump 104 and the
controller 106 are configured so that they can communicate with
each other using wireless communication channels 110a, 110b (e.g.,
using wireless communication technologies). However, in other
implementations, information may be transferred between the
components illustrated in FIG. 1 using a wired connection or may,
in some instances, be transferred by the user or caregiver him or
herself. For example, if the glucose measuring/monitoring device
102 is a monitor that simply presents blood glucose reading on a
visual display, for example, but is not able to transmit the
reading directly to the controller 106, the then the person using
the system 100 may view the displayed blood glucose reading and
enter that reading manually at the controller 106. In other
implementations (not shown), any one of the glucose
monitoring/measuring device 102, the insulin pump 104 and the
controller 106 can be combined with another of the devices in a
single integrated unit, or all three may be combined. In combined
devices, discretionary delivery protocols may be provided by a
dedicated computer-based processor, or a single processor may
control discretionary delivery protocols, glucose monitoring,
insulin delivery device functions and/or user interface
functions.
[0073] In various implementations, the glucose monitoring/measuring
device 102 can be a continuous glucose monitor, a blood glucose
meter, an intravenous blood glucose measurement device, or other
device adapted to provide an indication of blood glucose levels in
the user. In some implementations, the level of glucose in the
user's blood may never be directly measured. Rather, the glucose
level in the user's interstitial fluid or other bodily fluid or
tissue may be measured, and at some point may (or may not) be
converted into an equivalent glucose level of whole blood, plasma
or serum. It is to be understood that the use herein of the
terminology "blood glucose" level may mean actual blood glucose
level or a surrogate glucose level, depending on the context.
[0074] The insulin "pump" 104 can be any type of insulin delivery
device. In general, the insulin pump is a medical device used for
the administration of insulin, for example, in the treatment of
diabetes. The pump can have a variety of possible configurations.
In some implementations, for example, the insulin pump 104 includes
a pump (with controls, processing module, batteries, etc., a
disposable reservoir for insulin (which may be inside the pump),
and a disposable infusion set, including a cannula for subcutaneous
insertion (under the skin) and a tubing system to interface the
insulin reservoir to the cannula. In some implementations, however,
the pump may not include one or more of these components. For
example, in some implementations, the pump will not have tubing.
Also, in some implementations, the pump will not include a
disposable reservoir. In other configurations, the pump may be
controlled by a handheld device or by an application loaded onto a
mobile phone or other mobile computing device. It is to be
understood that, depending on the context, the use herein of the
terminology "pump" or "delivery device" may refer to conventional
insulin pumps available on the market today, or may refer to other
insulin delivery devices such as insulin pens, automated inhalers,
variable rate insulin skin patches and other such delivery devices,
whether or not they are commercially available today. It is
envisioned that the devices, systems and methods disclosed herein
may also be applied to other insulin delivery methods, such as
intravenous insulin delivery in an intensive care unit, and may
also find use in delivering other medicines or fluids to a user. In
such other systems, analyte(s) other than glucose may be monitored
in a user's body to aid in determining the desired amount of
medicine or fluid to be delivered to the user.
[0075] The controller 108 can be any type of computer-based device
configured to implement and/or facilitate the functionalities
disclosed herein. In some implementations, the controller 108 is a
smartphone executing the Android.TM. operating system. However, the
controller 108 can be any type of smartphone (or other device)
executing any type of operating system. In general, a smartphone is
a mobile phone built on a mobile operating system, with more
advanced computing capability connectivity than a feature phone.
Many modern smartphones also include high-resolution touchscreens
and web browsers that display web pages. High-speed data access can
be provided by Wi-Fi and/or mobile broadband.
[0076] Although shown as three separate components, the controller
106 and/or certain of its functionalities described herein can be
physically integrated into the glucose monitoring/measuring device
102 and/or the insulin pump 104.
[0077] FIG. 2 is a schematic diagram illustrating an exemplary
configuration of the controller 106.
[0078] The illustrated controller 106 has a processor 202, a
storage device 204, a memory 206 having software 208 stored therein
that defines certain aspects of the functionality disclosed herein,
input and output (I/O) devices 210 (or peripherals), and a local
bus, or local interface 212 allowing for communication among the
various components within the controller 106. The local interface
212 can be, for example, one or more buses or other wired or
wireless connections. The local interface 212 may have additional
elements, which are omitted for simplicity, such as controllers,
buffers (caches), drivers, repeaters, and receivers, to enable
communications. Further, the local interface 212 may include
address, control, and/or data connections to enable appropriate
communications among the aforementioned components.
[0079] The processor 202 is a hardware device for executing
software, for example, software 208 that is stored in the memory
206. The processor 202 can be any custom made or commercially
available single core or multi-core processor, a central processing
unit (CPU), an auxiliary processor among several processors
associated with the controller 106, a semiconductor based
microprocessor (in the form of a microchip or chip set), a
macroprocessor, or generally any device for executing software
instructions. For example, if the controller 106 is an Apple.RTM.
Iphone.RTM. 5 smartphone, then the processor 202 may be an
Apple.RTM. A6 APL0589, Dual Core 1.2 GHz processor.
[0080] The memory 206 can include any one or combination of
volatile memory elements (e.g., random access memory (RAM, such as
DRAM, SRAM, SDRAM, etc.)) and nonvolatile memory elements (e.g.,
ROM, hard drive, tape, CDROM, etc.). Moreover, the memory 206 may
incorporate electronic, magnetic, optical, and/or other types of
storage media. The memory 206 can have a distributed architecture,
where various components are situated remotely from one another,
but can be accessed by the processor 202.
[0081] In general, the software 208 defines one or more
functionalities that may be performed by the controller 106. The
software 208 in the memory 206 may include one or more separate
programs, each of which contains an ordered listing of executable
instructions for implementing logical functions of the controller
106. The memory 206 may contain the operating system (O/S) 520. The
operating system essentially controls the execution of programs
within the controller 106 and provides scheduling, input-output
control, file and data management, memory management, and
communication control and related services.
[0082] The I/O devices 210 may include input devices, such as a
keyboard, mouse, scanner, touchscreen, microphone, roller ball,
etc. Furthermore, the I/O devices 210 may also include output
devices, such as a display, an audio speaker, a vibrator, etc.
Finally, the I/O devices 210 may further include devices that
operate as both input and output devices, such as a
modulator/demodulator (modem; for accessing another device, system,
or network), a radio frequency (RF) or other type of transceiver, a
telephonic interface, a bridge, a router, or other
device/component.
[0083] In general, when the controller 106 is in operation, the
processor 202 executes software 208 stored in the memory 206,
communicates data to and from the memory 206, and generally directs
operations of the controller 106.
[0084] FIG. 3 is a flowchart showing one implementation of
facilitating delivery of insulin to a user. The illustrated method
may be implemented by the system 100 represented in FIGS. 1 and 2
and described herein.
[0085] In a typical implementation, the system 100 enables a person
(e.g., a user) to specify parameters associated with a
discretionary delivery of insulin that may be delivered to the
user. In some implementations, the system 100 enables the user or
caregiver to specify these parameters by enabling the person to
enter information at a user interface (e.g., by using the display
screen and/or a keypad at the controller 106).
[0086] So, for example, the system 100 may present to the person at
the display screen of the controller 106, a selectable icon that
provides the person with access to an interaction that enables the
person to specify these parameters. The parameters may identify,
for example, one or more specific time periods during which the
system 100 will be authorized to make a discretionary insulin
delivery, if warranted. In addition, the parameters may identify
various other aspects of the discretionary delivery authorization.
For example, in various implementations, the system may enable or
prompt the person to specify parameters that authorize
discretionary insulin deliveries of: [0087] up to X units in T
hours (with no constraint on rate of delivery); [0088] between X
and Y units delivered in T hours (with no constraint on rate of
delivery) between X and Y units in T hours with a delivery rate
constrained between A units/hr. and B units/hr. (note: A may or may
not equal 0); [0089] between X and Y units in T hours with a
delivery rate between A units/hr. and B units/hr. and where
X=[non-discretionary delivery over time T]-M and
Y=[non-discretionary delivery over time T]+N (this is an example of
#3 where X and Y are functions of the non-discretionary delivery
schedule); [0090] iteratively perform #4 periodically (e.g., every
5 minutes) evaluating based on the prior T hours; [0091] if the
discretionary delivery algorithm reaches the constraint of a
delivery equaling X or Y units of insulin during any T hour period,
then the discretionary delivery would end, non-discretionary
delivery would resume and an alarm and/or notification may be
sounded to alert the user/caregiver; [0092] in the case of 6, where
the maximum Y units of insulin have been delivered, if the person
does not acknowledge the alarm within a predetermined amount of
time (e.g., 5 minutes) then the system may attenuate subsequent
non-discretionary delivery of insulin for some amount of time to
offset some or all of the discretionary insulin delivery. This
offset amount, in some cases, may be equal to the difference
between the discretionary delivery and the non-discretionary
delivery that the discretionary delivery replaced; [0093] no
discretionary dosing over and above what the non-discretionary
delivery schedule calls for if the relative level of a user's
glucose level to insulin-on-board is below a particular value. See
FIG. 5; [0094] if the fraction of D minute sub-periods where more
than C units of insulin are delivered during a T hour period
exceeds a constraint F, then the discretionary delivery would end,
non-discretionary delivery would resume and an alarm and/or
notification may be sounded to alert the person (C may be a
constant or a function of the non-discretionary basal rate for each
sub-period); and/or [0095] in the case of 9, where the alarm is
triggered, if the person does not acknowledge the alarm within a
predetermined amount of time (e.g., 5 minutes) then the system may
attenuate subsequent non-discretionary delivery of insulin for some
amount of time to offset some or all of the discretionary insulin
delivery. This offset amount, in some cases, may be equal to the
difference between the discretionary delivery and the
non-discretionary delivery that the discretionary delivery
replaced.
[0096] In the scenarios set forth above, X, Y, T, A, B, C, D, M and
N are variables that can represent virtually any positive number or
zero. F represents a number between zero and one.
[0097] In some implementations, the system 100 enables (e.g.,
prompts) the user to specify other parameters or combinations of
these and/or other parameters as well. The parameters can authorize
discretionary delivery of insulin in terms of one or more basal
rates, one or more boluses or combinations thereof
[0098] Typically, the person is able to specify the parameters of a
discretionary delivery anytime (e.g., just before triggering
discretionary delivery mode, or any other time).
[0099] In a typical implementation, the system 100 stores any
parameters specified by the person, for example, in the memory
device 206 of the controller 106.
[0100] According to the illustrated implementation, the system 100
delivers (at 304) insulin to the user according to a
non-discretionary delivery schedule.
[0101] In general, the phrase "non-discretionary delivery schedule"
refers to a schedule that does not allow the system 100 to exercise
any discretion in delivering insulin to the user. So, for example,
a typical non-discretionary delivery schedule might include a
preprogrammed schedule for delivering insulin to a user over the
course of a day (e.g., 1 unit per hour, all day long) or longer as
well as any variations from that schedule (e.g., deliver 1 unit as
a bolus at 3 pm or non-discretionary extended boluses) that the
person instructs must happen. When operating according to a
non-discretionary delivery schedule, the system 100 is not
permitted to exercise any discretion in delivering insulin to the
user. It merely delivers an amount of insulin that is dictated by
non-discretionary delivery schedule.
[0102] In the absence of a trigger (e.g., at 306 in FIG. 3) to
enter a discretionary delivery mode, the system 100 simply
continues (at 304) to deliver insulin to the user according to the
non-discretionary delivery schedule.
[0103] However, if a trigger does occur (at 306), then, according
to the illustrated implementation, the processor 202 causes the
system 100 to implement (at 310) a discretionary delivery of
insulin. In some implementations, the insulin delivered pursuant to
the discretionary delivery is in addition to any insulin delivered
pursuant to the non-discretionary delivery schedule if the
non-discretionary delivery is not suspended in response to the
trigger. In some implementations, the insulin delivered pursuant to
the discretionary delivery is in lieu of some or all of the insulin
that would have been delivered pursuant to the non-discretionary
delivery schedule, if the non-discretionary delivery is suspended
in response to the trigger.
[0104] The trigger (at 306) can be virtually any kind of trigger.
For example, in some instances, the trigger may come from the
person pressing a button at the controller 106 to initiate a
discretionary delivery. In some instances, the trigger may come
from a timer indicating that a designated period of time where
discretionary delivery is authorized (e.g., 9:00 PM-6:00 AM) has
begun. In some instances, the trigger may come from the user's
blood glucose readings reaching a certain value. In some instances,
the trigger may relate to an amount of insulin that has been or
soon will be delivered to the user. In some instances, the trigger
may be in response to the person pressing a button indicating that
a meal is taking place or about to take place. The trigger may also
be based on the location of the user which may be ascertained by an
internal GPS system or by virtue of being within wireless
connectivity of a certain location based device (such as a
Bluetooth device or a Wi-Fi device).
[0105] The data that may cause the trigger can come from a variety
of different sources. For example, the user's blood glucose
readings may come from the glucose monitoring device 102 or may be
entered by the user directly into the controller 106 via its user
interface. The amount of insulin that has been delivered to the
user may come from the insulin pump 104. The amount of insulin that
soon will be delivered to the user can come from the
non-discretionary delivery schedule that may reside, for example,
on the insulin pump 104 and/or in the controller 106. The person's
button press (or the like) may come from the controller 106 or from
the insulin pump 104. The radio signal to determine a location may
come from a wireless access point or a Bluetooth device.
[0106] Some of this data e.g., the data that comes from the insulin
pump 104 or the glucose monitoring device 102 may travel to the
controller 106 (i.e., the processor 202 in the controller 106) via
the respective wireless communication channels 110b, 110a. In some
implementations, at least some of this data (e.g., blood glucose
readings) is transmitted to the processor 202 on a continuous,
substantially continuous, periodic or occasional basis.
[0107] As part of implementing the discretionary delivery (at 310),
the system 100 determines an amount of discretionary insulin and,
in some implementations, a precise time when that discretionary
insulin should be delivered to the user.
[0108] One way that the system 100 (e.g., the processor 202) might
make these kinds of determinations is by the processor 202 in the
controller 106 determining whether the user's blood glucose level
will, at some future point in time, likely move outside a range of
acceptable blood glucose levels.
[0109] In this regard, the graph in FIG. 7 shows a user's recent
blood glucose readings plotted against time. The graph shows that
the user's blood glucose level went up and down from the first
reading in the graph, taken at 7:00:00, until the last reading in
the graph, taken at 9:30:00. In the illustrated example, a new
reading was taken approximately every five minutes. The last five
readings in the illustrated graph show a gradual downward slope of
the user's blood glucose levels. The period beyond 9:30:00 in the
illustrated graph represents the future.
[0110] In some implementations, in order to determine whether the
user will likely benefit from a discretionary insulin delivery, the
processor 202 may project out into the future (represented by the
future region in the illustrated graph) a continuation of whatever
trend (e.g., slope) a most recent set of blood glucose readings
(e.g., 3, 4, 5 or more readings) indicate.
[0111] In the illustrated example, the most recent set of readings
(e.g., looking back about 15 minutes from the last reading in the
illustrated example) indicate a downward slope that, if projected
out 1 hour into the future would result in a blood glucose level
indicated by point 402. The 1 hour projection into the future is
represented in the illustrated example by a straight, solid line
that extends from a blood glucose reading of about 160 down to a
projected blood glucose reading of 105 (an hour after the 160
reading).
[0112] In different implementations, the number of past readings
that the processor considers to predict a future blood glucose
reading can vary from implementation to implementation. However, in
general, the readings used will typically start with the most
recent glucose reading and usually span over a time period of
between 5 minutes and 3 hours in the past.
[0113] The projected glucose reading may be calculated by
evaluating the trend or slope in log-space. That is, instead of
using the actual glucose values in the calculation above, the
logarithms of the glucose values are used to calculate the slope or
trend in values. Projecting out the logarithms of the glucose
values will give a logarithm of the projectedBG. This can be turned
into a projectedBG by exponentiating the logarithm of the
projectedBG.
[0114] For example, to calculate the projectedBG in log-space for
the illustrated example, one may take the natural logarithm (or any
other base logarithm) of all of the values in the graph in FIG. 7.
One may calculate the recent slope of the logarithm BGs and project
out the logarithm of the BG by extending the slope to the logarithm
of 160 (in the case of the natural logarithm, this value would be
.about.5.0751738), the current blood glucose level. In this
example, this results in a logarithm of the projectedBG which can
be used in the formula e (logProjectedBG) to obtain the actual
projectedBG.
[0115] In some implementations, after the processor 202 determines
a projected future blood glucose reading, it determines whether
that projected future blood glucose reading is acceptable or not.
In general, if the projected future blood glucose reading is
acceptable, then the system 100 may continue to deliver insulin to
the user according to the non-discretionary insulin delivery
schedule.
[0116] In some implementations, the system 100 stores the range of
acceptable readings for projected future blood glucose in memory
206. In those implementations, the processor 202 may determine if
the projected future blood glucose reading is within the acceptable
range by comparing the projected, future blood glucose reading with
the range of acceptable readings stored in memory 206.
[0117] Even more particularly, in some implementations, the
processor 202 calculates an error of the projected blood glucose
reading relative to a range of acceptable blood glucose readings
(stored, e.g., in memory 206). In that case, the error associated
with a projected actual blood glucose level (projectedBg) can be a
function of the projectedBG less an upper target of the target
range, if the projectedBG is greater than the upper value; the
error can be a function of the projectedBG less a lower target of
the target range, if the projectedBG is less than the lower target;
and the error would be zero if the projectedBG is greater than or
equal to the lower target and less than or equal to the upper
target.
[0118] In some implementations, the error calculated in this manner
may be used to determine what, if any, the discretionary delivery
should be. For example, if the magnitude of the error is zero (or
at least below some threshold value) then the system 100 may
exercise its discretion and decide to continue delivering insulin
in an amount equal to what the non-discretionary delivery schedule
would have called for as if a trigger had never occurred. If the
magnitude of the error is non-zero (or above the threshold value)
then, in certain implementations, the system 100 may use the
calculated error to determine what, if anything, the discretionary
insulin delivery should be.
[0119] In some implementations, the error may be computed as a
function of the logarithm of the target and predicted glucose
values. In such an implementation, the difference between the
logarithm of the projectedBG and the logarithm of the relevant
threshold target level (eg log(projectedBG)-log(target_threshold)
can be used to calculate the error.
[0120] The essence of the error used to calculate the dosing
adjustment is that the error increases as the difference between
the projectedBG value and the target range increases and the error
decreases as the difference between the projectedBG value and the
target range decreases. Note that the absolute value of the error
should increase as the projectedBG moves away from the target range
in either direction; the sign of the error is negative when the
projectedBG is less than the target range and its sign is positive
when the projectedBG is greater than the target range. Virtually
any function that meets these criteria can be used to implement
various implementations of the present disclosure.
[0121] Some implementations will create an adjusted-error based on
some weighted sum of the errors over a previous period of time.
This period of time may be virtually of any length. To calculate
the adjustment to the error, the past may be broken into a discreet
set of sub-periods, each with a corresponding error that was
calculated at the time. Each sub-period may have a weighting
associated with it; this weighting may be simple, such as equal
weighting, where the weighting is equal to 1 for every
sub-period.
[0122] In some implementations, the weighting may be a more complex
function such as an exponential decay function where the sub-period
weighting is assigned a value equal to e (-alpha*period) where
period is the number of sub-periods back from the current time and
alpha is some positive real number. For example, if the sub-periods
are five-minutes long, then a value for alpha of 0.03 would be a
reasonable value in some embodiments. Other implementations may use
arbitrary weighting schemes that may relate to the absorption
profile of the insulin or virtually any function that is
appropriate for the specific implementation.
[0123] Further, in some implementations, the periods used for
calculating the adjustment to the error may be limited to the
sub-periods that are between the current time and the most recent
period where the glucose values cross some threshold level or
levels (e.g. the top and bottom thresholds of a target glucose
range.) For example, if the current glucose is 180 mg/dL and the
single threshold is 120 mg/dL, then, under these circumstances, the
calculation of the adjustment to the error would only include
sub-periods between the current time and the most recent period
where the glucose value was below 120 mg/dL. If the current glucose
were 75 mg/dL, under the same circumstances, then the calculation
would only include sub-periods between the current time and the
most recent period where the glucose value was above 120 mg/dL.
[0124] In implementations that use the adjusted-error, the
adjusted-error used for discretionary dosing decisions may be
computed by summing the current instantaneous error of the system
and the adjustment to the error as described above.
[0125] There are a variety of other ways that the processor 202 may
(in implementing the discretionary delivery at 310) determine how
much or when to deliver a discretionary dose of insulin. In some
embodiments, the parameters of the discretionary delivery will
always be within the boundaries of whatever the person has
authorized. Additionally, under certain circumstances, the
parameters may be constrained by other restrictions (e.g.,
restrictions related to safety, such as that a particular minimum
amount of insulin must be delivered within a particular length of
time, that a rate of insulin delivery must not exceed some
specified maximum rate, etc.).
[0126] In some instances, the parameters may be equal to the
parameters entered by the person when he or she authorized the
discretionary delivery. In some implementations, certain of the
parameters may be constrained by one or more system constraints. In
some instances, the parameters may call for a greater or lesser
discretionary delivery depending, for example, on how far out of
the bounds of the acceptable range a projected future blood glucose
reading is. For example, in some implementations, the processor 202
multiplies the calculated error (between the projected future blood
glucose reading and the range of acceptable readings) by some gain
value and adds the result to the non-discretionary insulin delivery
schedule to produce, in effect, a discretionary insulin delivery.
An example of this is represented by the graph in FIG. 6. The gain
value can be a constant value or it can be a function of the
non-discretionary insulin delivery schedule such as a constant
multiplied by the non-discretionary delivery rate for the current
or future time.
[0127] In these instances, if a large adjustment is determined to
be warranted, then the resulting discretionary delivery would
reflect this; if, on the other hand, a small adjustment is
determined to be warranted, then the discretionary delivery would
reflect this.
There are a variety of other ways that the processor 202 can (as
part of 309) determine how much discretionary insulin to deliver
(i.e., make a dosing recommendation or identify parameters
associated with a discretionary delivery). For example, in some
implementations, the processor 202 can make a dosing recommendation
based on the user's latest blood glucose reading. Additionally, in
some implementations, the processor 202 can make a dosing
recommendation based on the user's latest blood glucose reading, a
target blood glucose level that may have been specified by the
person, and an estimated amount of insulin-on-board (IOB) for the
user. Making a dosing recommendation based on these parameters, can
include, for example, utilizing the following relationship:
dose.sub.--t=Max(0,
((BG_cur-BG_target)/(C.sub.--1*ISF))-(C.sub.--2*IOB)+C.sub.--3),
[0128] where dose_t represents a recommended dosing at time t (a
positive value or zero), [0129] BG_cur is the user's latest blood
glucose reading, BG_target represents a target blood glucose level
(or one or more outer boundaries of a range of acceptable blood
glucose readings), ISF represents the user's insulin sensitivity
factor and C.sub.--1, C.sub.--2, and C.sub.--3 are constants that
may be used to tune the equation according to how aggressively the
user wants to algorithm to run.
[0130] In a typical implementation, the insulin sensitivity factor
reflects an amount that the user's blood glucose is lowered by the
delivery of 1 unit of insulin. Insulin sensitivity can differ from
user to user and within a user on a diurnal basis and/or from day
to day.
Other possible ways that the processor 202 can make its dosing
recommendation include: making the dosing recommendation based on
an implied therapy using a fitting algorithm. Making the dosing
recommendation based on the implied therapy using the fitting
algorithm can include, for example, utilizing the following
relationship:
dose.sub.--t=Max(0,
(C.sub.--1*(BGcur-Bgtarg)/ISF)+(C.sub.--2*COB/carb_ratio)-(C.sub.--3*IOB)-
+C.sub.--4), [0131] where dose_t represents a recommended dosing at
time t (a positive value or zero), [0132] ISF represents the user's
insulin sensitivity factor, COB represents carbohydrates-on-board
for the user, carb_ratio represents the number of carbohydrates
that one unit of insulin offsets for that individual and C.sub.--1,
C.sub.--2, C.sub.--3 and C.sub.--4 are constants that may be used
to tune the equation according to how aggressively the user wants
to algorithm to run.
[0133] The phrase "carbohydrate-on-board," or COB, refers generally
to an estimated amount of carbohydrates that the user has ingested
into in his or her body but has not yet been absorbed. COB can be
calculated based on a variety of factors, including the amount of
carbohydrates recently ingested by the user, the time elapsed since
those ingestions, a carbohydrate absorption function and one or
more algorithms that estimate the remaining carbohydrates in the
body based on one or more of the following: the historical glucose
values, historical insulin dosing, and/or historical carbohydrate
ingestion events.
[0134] The processor 202 also can make a dosing recommendation
based on one or more of a target BG level, an IOB level, a
carbohydrate-on-board (COB) level, or a rate or change of BG (or
future predicted BG level), etc.
[0135] Predicting (or projecting) a future blood glucose reading
can be accomplished utilizing one or more of the following
approaches to extrapolate the future blood glucose reading: a
proportional-derivative algorithm; a proportional, integral,
derivative (PID) algorithm; an autoregressive forecasting model,
such as autoregressive integrated moving average (ARIMA) models; or
an algorithm based on physiological models of insulin and glucose
transport.
[0136] Autoregressive integrated moving average (ARIMA) models may
be parameterized on historical glucose data using techniques known
to those skilled in the art (software such as MATLAB, R, etc.
provide functions to perform such a parameterization). In
particular, an ARIMA(2,0,0) model also known as a second order
autoregressive model, AR(2), does a reasonable job of modeling
glucose levels. An AR(2) model may be used to create a projectedBG
in lieu of a linear or log-linear forecast described earlier. An
AR(2) model may fit the glucose data better by first
log-transforming and mean-centering the data. This may be done by
first taking the logarithm of the glucose data to create a time
series of log-glucose values. Mean centering is then accomplished
by subtracting the mean of all of the log-glucose values from each
individual log-glucose value to create the time series on which the
parameterization is performed.
[0137] AR(2) model forecasts may be created by iterating the AR
equation BG_t=a1*BG_t-1+a2*BG_t-2+epsilon_t, where a1 and a2 are
constants found in parameterizing the AR process and BG_t-x is the
BG x time periods prior to the current time and epsilon_t is the
error at any given point in time. To create the forecast, epsilons
are set to zero and the initial BG's are set from the two most
recent BG points. The process is repeated iteratively for each
period forward by replacing the BG_t+x with the most recent
projection and BG_t+x-1 with the second most recent projection. In
the case of log-transformed and mean-centered AR parameterizations,
the forecasts subsequently have the mean added back to the forecast
values and this sum exponentiated to arrive at the actual glucose
value forecasts.
[0138] Other algorithms for forecasting glucose levels include
modeling the physiological systems of insulin and glucose
transport. A number of compartmental models of glucose transport
are known to those skilled in the art. These models may be used to
forecast future glucose levels.
[0139] In essence, the processor 202 can implement any forecasting
algorithm to predict (project) a future blood glucose reading. This
projected glucose reading may then be used to calculate an error
and adjust the discretionary insulin dosing.
[0140] Referring again to FIG. 3, according to the illustrated
implementation, during the discretionary delivery, the processor
202 determines (at 312) if an alarm is warranted. In general, the
alarm, which may integrated into the controller 106 or the insulin
pump 104, for example, may provide an indication to the person that
any one or more of multiple different conditions has occurred.
These conditions can include, for example, that the amount of
insulin that has been delivered as the result of the system making
the discretionary delivery (in 310) exceeds some threshold value.
The threshold value in those implementations might be, for example,
equal to all (or most) of the insulin that has been authorized for
discretionary delivery to the user during the corresponding time
period. In other implementations, the threshold value might be, for
example, the fraction of sub-periods over a given time period where
insulin was increased by a certain amount. The alarm may be a
result of any one of multiple conditions that the user feels
constitutes a condition that warrants an alarm due to a large
amount of discretionary insulin delivery. This sort of alarm may be
referred to as a high delivery alarm.
[0141] If the processor 202 determines (at 312) that there is no
need to trigger an alarm and determines (at 314) that the
discretionary delivery is complete, then the system 100 reverts to
step 304 and delivers insulin to the user according to the
non-discretionary insulin delivery schedule.
[0142] If the processor 202 (at 312) determines that the alarm
should be triggered, the processor 202 (at 316) causes the alarm to
be triggered. The alarm can be audio, visual, tactile or a
combination thereof.
[0143] In some implementations, when triggered, the alarm provides
an indication to the person as to the condition or conditions that
caused the alarm to be triggered. This can be done in a variety of
ways. For example, a message may appear on a user interface screen
of the controller and/or pump indicating the cause of the
alarm.
[0144] Moreover, in some implementations, the system 100 provides
the person with the ability to acknowledge (and/or silence) the
triggered alarm. This may be done in a variety of ways as well. For
example, a touch sensitive "SILENCE ALARM" button may appear on the
user interface screen of the controller and/or pump while the alarm
is in a triggered state. Selection of the "SILENCE ALARM" button,
in those instances, may cause the alarm to become silenced. In
addition, in some implementations, the person's acknowledgement (or
silencing) of the alarm may be considered a verification to the
system 100 that the person considers the alarm condition (e.g., the
high delivery that caused a high delivery alarm) to be an
acceptable condition. In some implementations, one or more
verification or confirmation actions, which are separate from the
alarm silencing action, may be required to indicate to the system
100 that the person understands the alarm condition and considers
it to be an acceptable condition.
[0145] In some implementations, the processor 202 is configured to
determine (at 318) if the alarm has been acknowledged (e.g.
silenced) by the person in a timely manner (e.g., 30 seconds, 1
minute, 2 minutes, etc.).
[0146] According to the illustrated implementation, if (at 318) the
alarm is acknowledged (e.g., silenced) in a timely manner, then the
system 100, according to the illustrated example, reverts to step
304 and delivers insulin to the user according to the
non-discretionary delivery schedule.
[0147] In some implementations, if the alarm is acknowledged in a
timely manner, the system 100 subsequently delivers insulin to the
user according to a non-discretionary schedule of delivery,
according to a new, discretionary delivery schedule that the person
may subsequently be prompted to approve or enter or some
combination of both non-discretionary and discretionary
deliveries.
[0148] If the triggered alarm (at 316) is a high delivery alarm and
the alarm is not acknowledged (at 318) in a timely manner (e.g.,
because the person is sleeping or otherwise unable to acknowledge
the alarm), then, according to the illustrated implementation, the
system 100 subsequently and automatically (i.e., without specific
instructions from the person) delivers (at 320) less insulin to the
user than would be delivered if the system 100 were operating
according to the non-discretionary insulin delivery schedule.
[0149] In some implementations, subsequently delivering less
insulin than would be delivered according to the non-discretionary
schedule of delivery might include delivering an amount that is
between 0 and a multiple of the first threshold amount less than
what would be delivered according to the non-discretionary schedule
of delivery over a certain period of time. This can prevent the
excess insulin from incorrectly lowering blood glucose level or, in
some cases, allow glucose levels to revert from the lower levels
caused by unacknowledged additional discretionary dosing.
[0150] The first threshold amount can be, for example, a first
predetermined amount of insulin above what would have been
delivered to the user according to a non-discretionary delivery
schedule over the specific time period, and the second threshold
amount can be a second predetermined amount of insulin less than
what would have been delivered to the user according to the
non-discretionary delivery schedule over the specific time
period.
[0151] There are a variety of ways that the system 100 (e.g., the
processor 202) can determine how much the amount or rate of insulin
will be reduced following an unacknowledged alarm. Typically, the
reduction is such that it will, in a reasonable amount of time
(e.g., within 1-3 hours) at least partially (or entirely) offset
any extra insulin above the non-discretionary delivery the user may
have received as a result of the discretionary delivery. The
reduction can, in some implementations, be relative to whatever
amount or rate would be called for by the non-discretionary
delivery schedule.
[0152] If, at some point while the system is implementing step 320,
the reduction of insulin delivery relative to the non-discretionary
delivery schedule is deemed (e.g., by the processor 202) at 322 to
be sufficient to have offset enough of the maximum amount of
authorized discretionary insulin that was delivered to the user
(during 310), then the system 100 reverts to step 304 and delivers
insulin to the user according to the non-discretionary delivery
schedule. Otherwise, according to the illustrated implementation,
the system 100 keeps delivering less insulin to the user than the
non-discretionary delivery schedule would have called for.
[0153] In some implementations, the processor 202 (at 312)
determines whether the alarm is warranted based on whether a
cumulative amount of discretionary insulin delivered during a
specific time period has either exceeded a first threshold amount
or is below a second threshold amount. In some of those
implementations, the system 100 may be configured to trigger the
alarm (at 316) if either of these conditions exist.
[0154] In some implementations, the system 100 performs step 312 in
FIG. 3 (i.e., determining whether an alarm is warranted) on an
iterative basis. In this regard, the specific time period for which
data is considered for each iteration may be some period of time
prior to that iteration. For example, in one implementation, the
system 100 may be adapted to perform step 312 every five minutes,
based on a rolling four hour window of data. In that example, the
system 100 would make a new determination every five minutes as to
whether an alarm is warranted based on four hours of data preceding
when the new determination is being made. In the event of a
termination of discretionary delivery due to a breach in this
regard (i.e., a determination that an alarm is warranted), some
implementations cease all iterative steps as well.
[0155] FIG. 4 is a schematic diagram of an exemplary system 400
adapted to facilitate the functionalities disclosed herein for a
particular user and to communication or interact with one or more
pc-based web browsers 450 and client phones 452 over a wireless
network (having, e.g., a cloud-based server 456).
[0156] In some implementations, the exemplary system 400 in FIG. 4
has a similar structure and similar functionalities as the system
100 shown in FIG. 1. In exemplary system 400, the glucose
monitoring device 402 includes a sensor unit 408 that attaches to
the user, such as by adhering to the skin of the user, and a
handheld CGM controller unit 410. In this implementation, sensor
unit 408 has a transmitter that utilizes proprietary radio
frequency (RF) technology to communicate with the CGM controller
unit 410. The CGM controller unit 410 may include a processor for
receiving sensor data from sensor unit 408 and converting the
sensor data into corresponding blood glucose values. In some
implementations, CGM controller unit 410 includes additional
functionality, such as features that allow the glucose monitoring
device 402 to be calibrated, and a display screen to indicate blood
glucose values and/or trends to the user. The CGM controller unit
410 in turn communicates with controller 406. This communication
may be accomplished with a USB cable as shown, or through a
transmitter or transceiver in CGM controller unit 410 that
communicates with a corresponding receiver or transceiver at the
controller 406. In addition, the pump in this implementation uses
Bluetooth RF to communicate with the controller 406. The system 400
communicates to the cloud-based server 456 and the cloud-based
server 456 communicates with the pc-based web browsers 450 and the
client phones 452 using cellular or WiFi technology.
[0157] The specific communication technologies that the various
system components utilize can vary considerably. Additionally, the
function of each component shown in FIG. 4 may instead be performed
by multiple components, or two or more components shown may be
combined. For example, in some implementations (not shown), the
functionality of the CGM controller unit 410, the controller 406,
and the pump 404 may be combined in a single pump unit, such that
the CGM sensor unit 408 and the cloud-based server 456 communicate
directly with the single pump unit. In some implementations, the
sensor unit 408 may be combined with the infusion set (not shown)
that delivers insulin from the pump to the user through the user's
skin.
[0158] Other implementations may or may not include any cloud-based
components. In some implementations, a cloud-based server 456
transmits blood glucose values, trends, histories, alarm
conditions, non-discretionary and/or discretionary settings, and/or
other information from local system 400 to the cloud-based server,
web browsers 450 and/or mobile devices 452. In some embodiments,
information, settings, control commands and/or other information
may be transmitted from the web browsers 450 and/or mobile devices
452 to the cloud-based server and/or local system 400. In some
embodiments, some or all of these cloud-based communications may be
encrypted, limited with other security measures, or not provided at
all in order to reduce risk of inadvertent or intentional dosing
problems, for example.
[0159] Referring to FIG. 8, the illustration shows the operation of
an exemplary system that allows for adjusting basal rates between
zero and twice the non-discretionary, pre-programmed basal rate. In
other implementations, the minimum basal rate is greater than zero
and/or the maximum allowed basal rate is more or less than 200% of
the non-discretionary, pre-programmed basal rate. This exemplary
system provides for discretionary delivery of basal insulin in lieu
of the non-discretionary, pre-programmed basal rate.
[0160] The entire period depicted in the figure shows the system in
a discretionary delivery mode. The upper portion shows an example
of a user's blood glucose levels plotted against a time axis, and
the lower portion shows an associated insulin delivery rate
(represented by the shaded areas) to the user also plotted against
the same time axis. The solid line in the lower figure represents
the basal rate that the system desires to have set at any point in
time, and the top edge of the shaded region represents the basal
rate that was actually delivered. During various periods (for
example, 7:35-7:50) the solid line deviates from the top edge of
the shaded region (a dashed line in this time period) because the
controller 106 is unable to change the basal rate on the insulin
delivery device 104 due to communication errors in the system 100
(or 400). The dotted line at 0.8 U/hr on the lower portion
indicates the pre-programmed, non-discretionary basal rate. The
insulin delivery represented in the illustrated graph represents
how the system in FIG. 1, for example, might deliver insulin to the
user.
[0161] The blood glucose levels up until 9:45 AM represent actual
blood glucose readings (e.g., from a glucose monitoring device,
such as 102 in FIG. 1), whereas the blood glucose levels after 9:45
AM represent future blood glucose level predictions.
[0162] According to the illustrated time plot, up until about 8:15
AM, the delivery of insulin is largely responsive to the changes in
the user's blood glucose readings. As can be seen, slight
variations in the slope of the recent glucose values cause minor
decreases in the discretionary basal rate delivery during this
period. A glucose value increase at 7:35 warranted an increase in
basal rate delivery by the system; however, a communication problem
precluded the system from increasing the rate. Subsequently, at
7:50, the rate reverted to the non-discretionary basal rate since
the glucose level and rate of change indicated an in-target
predicted glucose level.
[0163] At about 8:15, there is an increase in the user's blood
glucose reading that might, under certain circumstances, suggest
that an increase in the delivery rate of insulin might be
appropriate. This increase in blood glucose reading may be a
response to the user ingesting carbohydrates, for example. More
particularly, at 8:15, in the illustrated example, the recent
upward trend in blood glucose readings suggests that, in the
future, the user's blood glucose level will be unacceptably
high.
[0164] However, as can be seen, there is no increase in the rate of
insulin delivery at 8:15 despite the fact that the recent upward
trend in blood glucose readings suggests that, in the future, the
user's blood glucose level will be unacceptably high. This is
because, in the illustrated example, the system 100 is constrained
from increasing the insulin delivery rate by the user's IOB
(insulin-on-board), for example by using the IOB constraints
described herein. In essence, the system 100 does not increase the
insulin delivery rate, even though the blood glucose readings show
an upward trend, because the user's IOB suggests that the insulin
already in the user's body may be sufficient to effectively manage
the recent upward trend in user's blood glucose readings. The
period of time during which the IOB constraint is in effect is
represented by the circle in the lower part of the time graph.
[0165] According to the illustrated example, the user's blood
glucose readings continue to increase while the system 100 is
constrained from increasing the insulin delivery rate by the user's
IOB.
[0166] Just before 9:00 AM, the system 100 increases the insulin
delivery rate. This increase is in response to the continuing
upward trend in blood glucose readings and the user's IOB
remaining. In essence, just before 9:00 AM in the illustrated
example, the user's blood glucose readings and IOB remaining cross
the IOB constraint threshold (as described in FIG. 5) to allow the
system 100 to allow augmented dosing to begin.
[0167] Throughout the discretionary delivery, the exemplary system
may iteratively perform alarm constraint checks, for example, to
see if the net amount of discretionary insulin dosed over the past
3 hours is greater than 1.5 units. In some implementations, this
check is done every 5 minutes. If the system determines (not shown)
that the net amount of discretionary insulin delivery over the past
3 hours is greater than the allowed amount of 1.5 units, the system
is configured in some implementations to take actions to alert and
potentially reverse any excess insulin delivered as described in
steps 316, 318, and 320 herein, shown in FIG. 3.
[0168] Referring back to FIG. 8, shortly after the augmented dosing
begins, the user's blood glucose readings hit a local maximum and
begin coming down. Once the projected future blood glucose readings
are within an acceptable target range (at about 9:25 AM), the
system 100 reverts the discretionary delivery to a level equal to
the non-discretionary basal rate. In this exemplary system, the
discretionary delivery will continue into the future until the user
manually terminates the discretionary delivery or a user constraint
(such as a maximum or minimum dosing constraint) is breached.
[0169] FIG. 9 provides another illustrated example of the operation
of an exemplary system that allows for adjusting basal rates
between zero and twice the non-discretionary, pre-programmed basal
rate in lieu of the non-discretionary, pre-programmed basal rate.
As in FIG. 8, the entire period shown is in discretionary delivery
mode. The upper portion shows an example of a user's blood glucose
levels plotted against a time axis, and the lower portion shows an
associated insulin delivery rate (represented by the shaded areas)
to the user also plotted against the same time axis. The solid line
in the lower figure represents the basal rate that the system
desires to have set, and the top edge of the shaded region
represents the basal rate that was actually delivered. During
various periods (for example, 9:50-9:55), the solid line deviates
from the top edge of the shaded region (a dashed line in this time
period) because the controller 106 is unable to change the basal
rate on the insulin delivery device 104 due to communication errors
in the system 100 (or 400). The dotted line at 0.8 U/hr on the
lower portion indicates the pre-programmed, non-discretionary basal
rate. The insulin delivery represented in the illustrated graph
represents how the system in FIG. 1, for example, might deliver
insulin to the user.
[0170] According to the illustrated plot, the insulin delivery is
attenuated to zero from 8:30 to 8:50 due to the low glucose level
and no indication from the rate of change of glucose level that it
will increase sufficiently.
[0171] At 8:55, a marked increase in the glucose level causes the
system to increase the basal rate to 1.6 U/hr--twice the
non-discretionary basal rate--in an attempt to avert a glucose
level above the desired range. This increase is held until the
glucose values crest around 9:45 in the target range.
[0172] At this point the system attempts to revert the basal rate
(at first unsuccessfully at 9:50, then with success at 9:55) to a
level close to the non-discretionary basal rate of 0.8 U/hr. This
level is short-lived, however, as the decrease in the level and
slope of the glucose values at 10:00 and beyond cause the system to
lower the discretionary delivery rate to 0 U/hr.
[0173] The rate of 0 U/hr will remain set until, at some future
point (not shown), the projected BG of the system indicates a level
closer to the target range or, in some implementations, until a low
dosing insulin alarm is triggered. A low dosing alarm occurs when
the amount of insulin delivered during a window of a discretionary
delivery period is less than a predetermined threshold value.
[0174] FIG. 10 provides an illustrated example of the benefit of
the high delivery alarm safety mitigation described herein at step
320 (as shown in FIG. 3). The figure shows a computer simulation of
a high delivery alarm 318 that is unacknowledged and where the
system 100 subsequently attenuates the delivery of the insulin at
320. In the illustrated example, the system is providing
discretionary delivery in lieu of the pre-programmed,
non-discretionary basal rate. The shaded areas show the time
varying adjustment to the non-discretionary basal rate as indicated
by the right y-axis in hours from the start of the simulation. In
this illustrated example, the non-discretionary basal rate is set
to 0.8 U/hr. Thus, the adjustment of 0.8 U/hr from time 0 to time
1.5 hours reflects an actual basal rate of 1.6 U/hr. Additionally,
the adjustment of -0.8 U/hr from time 1.5 hours to time 3 hours
reflects an actual basal rate of 0 U/hr.
[0175] The solid line shows a time varying plot of the
computer-simulated change in glucose level, as indicated by the
left y-axis in hours from the start of simulation. In this
exemplary system, the maximum discretionary insulin delivery amount
is set to the insulin that would be delivered in 1.5 hours of
pre-programmed, non-discretionary basal rate delivery which equals,
in this case, 1.2 units of insulin. As noted, a high delivery alarm
is set off at 1.5 hours when the maximum discretionary delivery
amount is reached. In the illustrated example, the alarm remains
unacknowledged, causing the system to enter into a removal of the
augmented delivery as described in step 320.
[0176] By delivering less than the pre-programmed,
non-discretionary basal rate, the system is effectively removing
insulin from the delivery profile. Because, as a part of the normal
course of insulin replacement therapy, the user needs the
pre-programmed basal insulin delivery to maintain a static glucose
level, the effect of delivering less than the pre-programmed
insulin rate results in a rise in the user's glucose level. The
difference between the pre-programmed basal delivery and the actual
insulin delivery is effectively insulin that is "removed" from the
user with the expected rise in glucose values equal to the absolute
value of the expected decline that the removed amount of insulin
would reduce the user's glucose levels.
[0177] Referring back to FIG. 10, after the alarm is triggered the
glucose level continues to drop for about an hour after which it
levels off and then begins to increase reflecting the effect of the
removed insulin. At the end of the simulation, the glucose level
has reverted to the original level before any adjustments to the
system had been made.
[0178] As can be seen from this example, the subsequent removal of
discretionary delivery upon an unacknowledged maximum dosing alarm
provides a robust safety mitigation to a possible unintended
over-delivery of insulin by a discretionary delivery system. The
benefits for a user of such a system are obvious including
mitigation of potentially extended, unintended, and possibly severe
hypoglycemia.
[0179] Referring to FIG. 11, another exemplary system is shown that
doses insulin in addition to a non-discretionary basal rate. This
exemplary system allows for constrained discretionary boluses; the
discretionary boluses in the system allow for a maximum rate of
delivery, maximum amount and maximum time to deliver the insulin.
In some implementations, the discretionary bolus includes an IOB
constraint.
[0180] The illustrated example shows how, in one implementation,
the system may use its discretion to deliver a 1 unit discretionary
bolus. In the figure, the dotted line plotted on the left y-axis is
the glucose level of the user. The solid shaded area on the bottom
of the graph reflects discretionary insulin deliver rates over time
as defined by the right y-axis. This discretionary insulin delivery
is in addition to the non-discretionary, pre-programmed basal rate
that the system continues to deliver throughout the discretionary
bolus delivery.
[0181] Referring to FIG. 11, a meal occurs at or around 11:30 that
includes the ingestion of carbohydrates and the need to dose
insulin to offset them. In the illustrated example, the user doses
a non-discretionary bolus of 3 units to cover the insulin
requirements of the majority of the meal and additionally doses a
discretionary bolus of 1 unit to be delivered over at most 3 hours
with a delivery rate not to exceed 1.5 U/hr or 150% of the user's
pre-programmed, non-discretionary basal rate of 1 U/hr. The user
sets this discretionary bolus to include an IOB constraint such
that discretionary insulin will only be delivered if the user
constraint of IOB vs glucose level is met.
[0182] In some situations, a user may desire to bolus for their
meal in this way if, for example, the user is uncertain as to how
much insulin will be required for the meal. In this case, the user
may bolus for the minimum amount of insulin he or she is confident
will be needed and then use a discretionary bolus for the amount
that may or may not be additionally needed. In this illustrated
example, the non-discretionary bolus is 3 units and the
discretionary bolus delivery is between 0 and a maximum of 1 unit
with the constraints detailed above.
[0183] Referring back to FIG. 11, the user's glucose level starts
to increase around 11:45 due to the ingestion of the meal. From
11:45 to 12:20, the glucose trends indicates that the system
should, in some implementations, deliver some of the discretionary
insulin bolus, however, due to the IOB constraint the discretionary
delivery is not made during this period. The period where the IOB
constraint is in effect is shown by a circle in the diagram.
[0184] At 12:20, the IOB constraint is breached and the system
begins to deliver the discretionary bolus. The infusion rate at
which the bolus is delivered increases as the glucose level and
slope of the glucose level increase until the delivery rate hits
the maximum allowable delivery rate of 1.5 U/hr at 13:05. Despite
the system desiring to increase the delivery rate higher than 1.5
U/hr, the maximum delivery rate constraint prevents it from doing
so.
[0185] At 13:35 the cumulative sum of the discretionary insulin
delivery reaches the maximum allocated amount of 1 unit. After this
occurs, the discretionary delivery mode ceases and the system
reverts back to non-discretionary mode where it continues to dose
the pre-programmed basal rate and other non-discretionary requests
that are made by the user.
[0186] FIG. 12 illustrates another exemplary system that doses
discretionary insulin in addition to a non-discretionary basal
rate. Similar to the system in FIG. 11, this exemplary system
allows for constrained discretionary boluses; the system allows for
a maximum rate of delivery, maximum amount of insulin and maximum
time to deliver the insulin. In some implementations, the system
allows for an additional time constraint for the earliest that the
discretionary delivery can occur.
[0187] The illustrated example shows how, in some implementations,
the system may use its discretion to deliver a 1 unit discretionary
bolus. In the figure, the solid line plotted on the left y-axis is
the glucose level of the user. The solid shaded area on the bottom
of the graph reflects discretionary insulin deliver rates over time
as defined by the right y-axis. This discretionary insulin delivery
is in addition to the non-discretionary, pre-programmed basal rate
that the system delivers.
[0188] Referring to FIG. 12, a meal occurs at or around 11:30. The
user doses a non-discretionary bolus to cover the insulin
requirements of the majority of the meal and additionally doses a
discretionary bolus of 1 unit to be delivered only between 2 and
3.5 hours later with a delivery rate not to exceed 1.5 U/hr or 150%
of the user's pre-programmed, non-discretionary basal rate of 1
U/hr.
[0189] In this exemplary situation, the user may choose to delay
the start of the discretionary delivery due to the composition of
the meal he or she is consuming. High fat meals such as pizza may
have delayed absorption potentially requiring insulin significantly
later than when the meal occurs. In this illustrated example, the
user choses to give a discretionary bolus 2 hours in the future,
when, for example, the user may see an increase in glucose levels
as a result of this delayed absorption.
[0190] Referring again to FIG. 12, we see that no discretionary
insulin is delivered prior to 13:30 despite elevated glucose levels
per the 2 hour minimum delay constraint. At 13:30, the system
implements a discretionary delivery of 1.5 U/hr, the maximum
allowed by the constraints of the discretionary bolus due to the
high level of projected glucose. As the glucose levels decline
around 14:00, the discretionary delivery rate decreases until the
system ceases discretionary delivery at 14:05. The system does not
dose any more insulin throughout the remainder of the discretionary
delivery period.
[0191] The total insulin delivered for this discretionary bolus is
0.7 units which is less than the maximum amount allowed of 1 unit.
At 15:00, the discretionary delivery period ends and the system
continues forward by dosing the pre-programmed basal rate and other
non-discretionary requests that are made by the user.
[0192] A number of embodiments of the present disclosure have been
described. Nevertheless, it will be understood that various
modifications may be made without departing from the spirit and
scope of the disclosure.
[0193] For example, this specification contains many specific
implementation details. However, these should not be construed as
limitations on the scope of any inventions or of what may be
claimed, but rather as descriptions of features specific to
particular embodiments of the present disclosure. Certain features
that are described in this specification in the context of separate
embodiments can also be implemented in combination in a single
embodiment. Conversely, various features that are described in the
context of a single embodiment can also be implemented in multiple
embodiments separately or in any suitable subcombination. Moreover,
although features may be described above as acting in certain
combinations and even initially claimed as such, one or more
features from a claimed combination can in some cases be excised
from the combination, and the claimed combination may be directed
to a subcombination or variation of a subcombination.
[0194] Similarly, while operations are depicted in the drawings in
a particular order, this should not be understood as requiring that
such operations be performed in the particular order shown or in
sequential order, or that all illustrated operations be performed,
to achieve desirable results. In certain circumstances,
multitasking and parallel processing may be advantageous. Moreover,
the separation of various system components in the embodiments
described above should not be understood as requiring such
separation in all embodiments, and it should be understood that the
described program components and systems can generally be
integrated together in a single software product or packaged into
multiple software products.
[0195] Processors suitable for the execution of a computer program
include, by way of example, both general and special purpose
microprocessor structures, and any one or more processors of any
kind of digital computer. Generally, a processor will receive
instructions and data from a read-only memory or a random access
memory or both. The elements of a computer are a processor for
performing actions in accordance with instructions and one or more
memory devices for storing instructions and data. Generally, a
computer will also include, or be operatively coupled to receive
data from or transfer data to, or both, one or more mass storage
devices for storing data, e.g., magnetic, magneto-optical disks, or
optical disks. However, a computer need not have such devices.
Moreover, a computer can be embedded in another device, e.g., an
insulin pump, an electronic pump controller, a continuous glucose
monitor, a mobile telephone or a personal digital assistant (PDA),
to name just a few.
[0196] Devices suitable for storing computer program instructions
and data include all forms of non-volatile memory, media and memory
devices, including by way of example semiconductor memory devices,
e.g., EPROM, EEPROM, and flash memory devices; magnetic disks,
e.g., internal hard disks or removable disks; magneto-optical
disks; and CD-ROM and DVD-ROM disks. The processor and the memory
can be supplemented by, or incorporated in, special purpose logic
circuitry.
[0197] To provide for interaction with a user, embodiments of the
subject matter described in this specification can be implemented
on a computer having a display device, e.g., a CRT (cathode ray
tube) or LCD (liquid crystal display) monitor, for displaying
information to the user and a keyboard and a pointing device, e.g.,
a mouse or a trackball, by which the user can provide input to the
computer. Other kinds of devices can be used to provide for
interaction with a user as well; for example, feedback provided to
the user can be any form of sensory feedback, e.g., visual
feedback, auditory feedback, or tactile feedback; and input from
the user can be received in any form, including acoustic, speech,
or tactile input. In addition, a computer can interact with a user
by sending documents to and receiving documents from a device that
is used by the user; for example, by sending web pages to a web
browser on a user's client device in response to requests received
from the web browser. Thus, a user interface of the inventive
systems and methods described herein may be remote from a
computer-based processor of the system, and may be operated by a
user and/or a caregiver.
[0198] Aspects of the disclosure can take the form of an entirely
hardware embodiment, an entirely software embodiment or an
embodiment containing both hardware and software elements. In some
embodiments, aspects of the disclosure are implemented in software,
which includes but is not limited to firmware, resident software,
microcode, etc. Furthermore, the aspects of the disclosure can take
the form of a computer program product accessible from a
computer-usable or computer-readable medium providing program code
for use by or in connection with a computer or any instruction
execution system. For the purposes of this description, a
computer-usable or computer readable medium can be any tangible
apparatus that can contain, store, communicate, propagate, or
transport the program for use by or in connection with the
instruction execution system, apparatus, or device.
[0199] As used herein, a computer-readable medium or
computer-readable storage medium, or the like, is intended to
include hardware (e.g., registers, random access memory (RAM),
non-volatile (NV) storage, to name a few), but may or may not be
limited to hardware. The medium can be an electronic, magnetic,
optical, electromagnetic, infrared, or semiconductor system (or
apparatus or device) or a propagation medium. Examples of a
computer-readable medium include a semiconductor or solid state
memory, magnetic tape, a removable computer diskette, a random
access memory (RAM), a read-only memory (ROM), a rigid magnetic
disk and an optical disk. Current examples of optical disks include
compact disk-read only memory (CD-ROM), compact disk-read/write
(CD-R/W). Some portions of the detailed description may be
presented in terms of algorithms and symbolic representations of
operations on data or data bits that may be, for example, within a
computer memory. An algorithm is here, and generally, conceived to
be a self-consistent sequence of operations leading to a desired
result. The operations are those requiring physical manipulations
of physical quantities. Usually, though not necessarily, these
quantities take the form of electrical or magnetic signals capable
of being stored, transferred, combined, compared, and otherwise
manipulated. It has proven convenient at times, principally for
reasons of common usage, to refer to these signals as bits, values,
elements, symbols, characters, terms, numbers, or the like.
[0200] It should be borne in mind, however, that these and similar
terms are to be associated with the appropriate physical quantities
and are merely convenient labels applied to these quantities.
Unless specifically stated otherwise or as apparent from context,
it is appreciated that throughout the description, discussions
utilizing terms such as "processing" or "computing" or
"calculating" or "determining" or "displaying" or the like, refer
to the action and processes of a computer system, or similar
electronic computing device, computer-based processor, etc. that
manipulates and transforms data represented as physical
(electronic) quantities within the computer system's registers and
memories into other data similarly represented as physical
quantities within the computer system memories or registers or
other such information storage, transmission or display
devices.
[0201] Other embodiments are within the scope of the following
claims.
* * * * *