U.S. patent application number 13/626521 was filed with the patent office on 2014-03-27 for information processing method.
This patent application is currently assigned to GOOGLE INC.. The applicant listed for this patent is Babak Amirparviz, Ehsan Saeedi. Invention is credited to Babak Amirparviz, Ehsan Saeedi.
Application Number | 20140088372 13/626521 |
Document ID | / |
Family ID | 50339518 |
Filed Date | 2014-03-27 |
United States Patent
Application |
20140088372 |
Kind Code |
A1 |
Saeedi; Ehsan ; et
al. |
March 27, 2014 |
INFORMATION PROCESSING METHOD
Abstract
Systems, apparatus and methods including a contact lens that
facilitates collection and/or processing of information associated
with sensed features are provided. In one aspect, a system can
include a contact lens and an analysis component external to the
contact lens. The contact lens can include: a substrate; and a
circuit, disposed on or within the substrate. The circuit can
include: a plurality of sensors configured to sense respective
features associated with a wearer of the contact lens; and a
communication component configured to communicate information
indicative of sensed features. The analysis component can be
configured to: receive the information indicative of the sensed
features; and generate statistical information based, at least, on
the information indicative of the sensed features.
Inventors: |
Saeedi; Ehsan; (Santa Clara,
CA) ; Amirparviz; Babak; (Mountain View, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Saeedi; Ehsan
Amirparviz; Babak |
Santa Clara
Mountain View |
CA
CA |
US
US |
|
|
Assignee: |
GOOGLE INC.
Mountain View
CA
|
Family ID: |
50339518 |
Appl. No.: |
13/626521 |
Filed: |
September 25, 2012 |
Current U.S.
Class: |
600/301 ;
600/300; 600/345; 600/347; 600/361; 600/549; 702/179 |
Current CPC
Class: |
G01K 13/002 20130101;
A61B 5/01 20130101; A61B 5/14539 20130101; G16H 50/20 20180101;
A61B 5/14532 20130101; A61B 5/6821 20130101; G16H 40/67 20180101;
A61B 5/002 20130101; G16B 99/00 20190201; A61B 5/1477 20130101;
A61B 5/6803 20130101; G02C 7/04 20130101 |
Class at
Publication: |
600/301 ;
600/300; 600/345; 600/347; 600/549; 600/361; 702/179 |
International
Class: |
A61B 5/1477 20060101
A61B005/1477; A61B 5/01 20060101 A61B005/01; G06F 17/18 20060101
G06F017/18; A61B 5/00 20060101 A61B005/00 |
Claims
1. An analysis component, comprising: a memory configured to store
computer executable components; and a processor configured to
execute the following computer executable components stored in the
memory: a communication component configured to receive, from a
contact lens, information indicative of features sensed on the
contact lens, wherein the features sensed on the contact lens are
features of a wearer of the contact lens; and a statistical
analysis component configured to generate statistical information
based, at least, on the information indicative of features sensed
on the contact lens.
2. The analysis component of claim 1, wherein generation of the
statistical information is based, at least, on regression
analysis.
3. The analysis component of claim 1, wherein the communication
component is further configured to receive information indicative
of a general health condition of the wearer of the contact lens,
and wherein the statistical analysis component is further
configured to at least one of: predict a future health condition or
make a recommendation based, at least, on the information
indicative of features sensed on the contact lens and the
information indicative of a general health condition of a wearer of
the contact lens.
4. The analysis component of claim 1, wherein the statistical
information comprises information indicative of at least one of
variation over time in one or more features sensed or an absolute
amount of one or more features sensed.
5. The system of claim 1, wherein at least one of the features
sensed comprises a potential hydrogen (pH) level, a temperature
level or a concentration of an analyte in a body of the wearer of
the contact lens.
6. A contact lens, comprising: a substrate; and a circuit
comprising: a plurality of sensors configured to sense respective
features associated with a wearer of the contact lens, wherein the
plurality of sensors are configured to be powered by a portable
radio frequency (RF) device external to the contact lens; and a
communication component configured to transmit, to the RF device,
at least, one of: information indicative of sensed features or a
recommendation based on the information indicative of sensed
features.
7. The contact lens of claim 6, wherein the recommendation
comprises information indicative of a service adapted to provide
dietary options or healthcare to the wearer of the contact lens,
wherein the recommendation is based, at least, on the information
indicative of sensed features.
8. The contact lens of claim 7, wherein the contact lens is further
configured to: transmit the information indicative of sensed
features to an analysis component configured to generate
statistical information based, at least, on sensed features; and
receive the statistical information from the analysis component,
wherein the statistical information comprises information
associated with the recommendation.
9. A method, comprising: receiving power, at a plurality of sensors
on a contact lens, from a device external to the contact lens;
sensing, via the plurality of sensors, a respective plurality of
features associated with a wearer of the contact lens; and
transmitting, from the contact lens, information indicative of
sensed features, to an analysis component configured to perform
statistical analysis on the information indicative of sensed
features.
10. The method of claim 9, wherein the receiving is performed
during a predefined time interval, and the sensing is performed
during the predefined time interval during which the power is
received.
11. The method of claim 9, wherein the plurality of features
comprise at least one of cholesterol concentration, glucose
concentration, temperature level or potential hydrogen (pH)
level.
12. The method of claim 9, wherein the receiving from the device
comprises receiving from at least one device selected from the
group consisting of smart phone, tablet computer, laptop,
head-mounted display device, and radio frequency (RF) reader.
13. The method of claim 9, wherein the statistical analysis
comprises at least one of regression analysis or generation of
information associated with a prediction or inference regarding a
health condition of the wearer of the contact lens.
14. A system, comprising: a contact lens, comprising: a substrate;
and a circuit, disposed on or within the substrate, and comprising:
a plurality of sensors configured to sense respective features
associated with a wearer of the contact lens; and a communication
component configured to communicate information indicative of
sensed features; and an analysis component, external to the contact
lens, and configured to: receive the information indicative of
sensed features; and generate statistical information based, at
least, on the information indicative of sensed features.
15. The system of claim 14, further comprising a device external to
the contact lens and configured to power the plurality of sensors
for a predefined time interval.
16. The system of claim 15, wherein the device is at least one of a
head-mounted display device, a smart phone or a laptop associated
with the wearer of the contact lens.
17. The system of claim 15, wherein the plurality of sensors are
further configured to sense the respective features during the
predefined time interval during which the plurality of sensors are
powered by the device.
18. The system of claim 15, wherein the device is further
configured to receive general health information input by the
wearer of the contact lens.
19. The system of claim 18, wherein the analysis component is
further configured to perform statistical analysis based, at least,
on the general health information input by the wearer of the
contact lens.
20. The system of claim 18, wherein the statistical information
comprises information generated based, at least, on regression
analysis of the information indicative of sensed features and the
general health information input by the wearer of the contact
lens.
21. The system of claim 14, wherein the analysis component is
further configured to generate information indicative of a
recommendation of nutritional food intake, wherein the
recommendation of nutritional food intake is based, at least, on
the statistical information.
22. The system of claim 14, wherein the analysis component is
further configured to generate information indicative of a
prediction associated with a health condition for the wearer of the
contact lens, wherein the prediction is based, at least, on the
statistical information.
Description
TECHNICAL FIELD
[0001] This disclosure generally relates to contact lenses that
facilitate collection and/or processing of information.
BRIEF DESCRIPTION OF THE DRAWINGS
[0002] FIG. 1 is an illustration of a block diagram of an exemplary
non-limiting system including a contact lens that facilitates
collection and/or processing of information in accordance with
aspects described herein.
[0003] FIG. 2 is an illustration of an exemplary non-limiting data
storage of a contact lens that facilitates collection and/or
processing of information in accordance with aspects described
herein.
[0004] FIG. 3 is an illustration of an exemplary non-limiting table
of information stored in a contact lens in accordance with aspects
described herein.
[0005] FIG. 4 is an illustration of an exemplary non-limiting
diagram of an analysis component that facilitates processing of
information in accordance with aspects described herein.
[0006] FIG. 5 is an illustration of an exemplary non-limiting graph
detailing statistical information generated by an analysis
component in accordance with aspects described herein.
[0007] FIGS. 6 and 7 are illustrations of exemplary non-limiting
flow diagrams of methods of operation for a contact lens that
facilitates collection and/or processing of information in
accordance with aspects described herein.
[0008] FIG. 8 is an illustration of a schematic diagram of an
exemplary networked or distributed computing environment with which
one or more aspects described herein can be associated.
[0009] FIG. 9 is an illustration of a schematic diagram of an
exemplary computing environment with which one or more aspects
described herein can be associated.
DETAILED DESCRIPTION
[0010] Various aspects are now described with reference to the
drawings, wherein like reference numerals are used to refer to like
elements throughout. In the following description, for purposes of
explanation, numerous specific details are set forth in order to
provide a more thorough understanding of one or more aspects. It is
evident, however, that such aspects can be practiced without these
specific details. In other instances, structures and devices are
shown in block diagram form in order to facilitate describing one
or more aspects.
[0011] Amperometry is the use of electric current or change in
electric current to detect analytes in a solution. The analyte can
include, but is not limited to, glucose, cholesterol, lactate, urea
or the like. Specifically, amperometry is performed using
amperometric electrochemical sensors with electrodes placed in
close proximity to the substance being analyzed. The measurements
from the electrode are based on an oxidizing or reducing reaction
that occurs when the electrode is in proximity to the substance.
Proper potentials applied to the electrodes cause such oxidizing or
reducing reactions to occur. The resulting electrical currents can
be employed in identifying the analyte in some embodiments.
[0012] Amperometric sensors require additional biosensing elements
on the working electrode in order for the current-generating redox
reaction to occur. One type of biosensing element is oxidase enzyme
that catalyzes the oxidation of analytes by oxygen. For example,
glucose oxidase can be deposited onto the sensor to enable the
sensor to detect glucose.
[0013] Amperometry is performed employing an electrochemical
sensor. When none of the substance being sensed touches the
electrodes of the sensor, no current flows. However, when the
substance being sensed touches the electrodes of the sensor,
current is generated and flows. The current can be measured to
determine the presence and/or concentration of the analyte in the
fluid. For example, the level of concentration of the material can
correspond to the measured current flow.
[0014] A number of different technologies can be employed in
producing the above-referenced electrodes. For example, for noble
metal thin film electrodes, vacuum deposition including sputtering
and evaporation can be employed. These steps can be combined with
photolithographic techniques to mask and pattern specific
electrodes and connections to the electrodes. For carbon
electrodes, screen printing of carbon ink can be employed.
[0015] Cholesterol is present in human eyes and tears. In some
extreme cases of very high cholesterol levels in the body, for
example, cholesterol accumulates and deposits around an eye lid to
form tiny yellow bumps called xanthelasma palpebra. However,
undesirable accumulation of cholesterol and excessive consumption
of cholesterol-containing food can result in serious
life-threatening conditions. For example, coronary heart diseases,
cerebral thrombosis, and artherosclerosis are associated with dense
accumulation of cholesterol in arterial walls.
[0016] Cholesterol concentrations are typically measured in
milligrams per deciliter (mg/dL) of blood. There are three
different categories of cholesterol levels: total cholesterol
level, High Density Lipoprotein (HDL) cholesterol level and Low
Density Lipoprotein (LDL) cholesterol level.
[0017] For total cholesterol levels, concentration less than 200
mg/dL is desirable and is considered lower risk for coronary heart
disease. A total cholesterol concentration of 200 mg/dL or higher
results in an elevated risk for coronary heart disease. Total
cholesterol concentrations between 200-239 mg/dL are borderline
high levels and cholesterol concentrations at and greater than 240
mg/dL are high cholesterol levels.
[0018] For HDL cholesterol levels, higher levels result in less
risk of coronary heart disease. HDL concentrations less than 40-50
mg/dL result in high risk for heart disease, while HDL
concentrations between 50-60 mg/dL are desirable.
[0019] For LDL cholesterol levels, lower levels result in less risk
of coronary heart disease. LDL concentrations less than 100 mg/dL
are optimal, LDL concentrations between 100-129 mg/dL are near or
above optimal level, LDL concentrations from 130-159 mg/dL are
borderline high level, LDL concentrations from 160-189 mg/dL are
high level and LDL concentration at 190 mg/dL and higher are very
high level.
[0020] Monitoring cholesterol and treatment of diseases associated
with high total cholesterol are invasive and time-consuming as
patients often have to visit the office of a medical provider for a
health physical or procedure.
[0021] Abnormally high or low glucose levels in the body are
associated with multiple health problems including diabetes
mellitus and damage to organs. A normal glucose level is considered
to be less than 100 mg/dL when fasting and less than 140 mg/dL two
hours after eating.
[0022] The diagnosis of diabetes or pre-diabetes is based on the
glucose level in the body. For example, a person can be diagnosed
with diabetes mellitus if his/her glucose level is higher than 126
mg/dL after fasting for eight hours, if his/her glucose level is
higher than 200 mg/dL two hours after drinking a special sugary
drink offered by a medical provider and/or if the glucose level is
200 and he/she has increased urination, thirst and/or weight
loss.
[0023] In conventional approaches, a daily routine involving finger
sticks is required and the corresponding discomfort and
inconvenience is regularly-occurring. However, a typical human tear
can contain enough glucose for measurement of blood glucose level
and the inconvenience and discomfort of finger sticks can be
avoided or minimized in the monitoring and diagnosis of diabetes
mellitus.
[0024] Potential hydrogen (pH) is the hydrogen ion level in the
body. The higher the pH level, the more alkaline and oxygen rich
the body. By contrast, the lower the pH level, the more acidic and
oxygen deprived the body. A typical pH level range is from 0 to 14,
with 7.0 being neutral. Levels above 7.0 are considered alkaline
and levels below 7.0 are considered acidic.
[0025] Human blood is typically within the range between 7.35 and
7.45 with the ideal human blood pH level being slightly alkaline at
a level of 7.4. Levels below or above this range can indicate
disease or other health concerns (e.g., cardiovascular weakness,
immune deficiency, free radical damage, stressed
bladder/kidney/liver function, cancer, low energy, weight
gain/loss, hormone concerns). Further, acidic blood can decrease
the body's ability to properly absorb nutrients, decrease the
ability of the body to repair damaged cells and detoxify heavy
metals and/or can make tumor cells thrive.
[0026] The pH level in the body can be measured from numerous
different bodily fluids (e.g., tear fluids, urine and saliva).
Accordingly, invasive blood tests are both cumbersome and
unnecessary.
[0027] The normal body temperature of a healthy, resting adult
human is approximately 98.6.degree. Fahrenheit (F.). However, body
temperature varies due to metabolism, with a higher metabolism
resulting in higher temperature and a lower metabolism resulting in
lower temperature. Time of day and day of month can also affect
body temperature. For example, the body temperature is lower in the
morning than in the evening. Body temperature also varies depending
on the part of the body in which it is measured. Oral temperatures
are typically 98.6.degree. F., axillary temperatures are typically
97.6.degree. F. and rectal temperatures are typically 99.6.degree.
F. The body temperature can also be measured in other areas (e.g.,
from the eye).
[0028] An elevated body temperature is typically indicative of
illness as the body tries to fight off fungi, viruses and bacteria
by raising the body temperature to a level in which germs and
toxins associated with the illness cannot thrive. Accordingly,
monitoring the body temperature can be an important part of
preventative health.
[0029] Statistics involves the collection, organization, analysis,
interpretation, and/or presentation of measured/collected
information. With advances in technology, more extensive and
complex computing allows massive amounts of data to be collected,
stored and/or processed. Further, methods for evaluating the data
are numerous.
[0030] Statistical analysis can be employed to process and/or
evaluate information (e.g., levels of cholesterol, glucose, pH
and/or temperature) sensed. The two main types of statistics are
descriptive and inferential statistics.
[0031] Descriptive statistics includes methods for organizing and
summarizing collected data. These methods include, but are not
limited to, graphs, tables, charts and measurements such as
averages, percentiles, and measures of variation of the data. Data
mining for pattern detection, machine learning and artificial
intelligence methods, regression modeling and summary statistics
can be employed in descriptive statistics.
[0032] Inferential statistics is based on methods for making
conclusions about data collected based on the evaluation of a
sample of the data. For example, predictions can be made regarding
the entire set of data. An example prediction can relate to the
likelihood that a disease or illness exists based on data collected
(e.g., cancer screening). Recommendations can be made to achieve or
avoid predictions.
[0033] Statistical methods such as regression analysis can be
employed to analyze data. Regression analysis includes techniques
for analyzing different variables to determine the relationship
between one or more dependent variables (e.g., cholesterol level)
and independent variables (e.g., lethargy). For example, the
analysis can be employed to determine how the value of a dependent
variable changes when a value of one independent variable changes
while keeping the values of other independent variables constant.
Regression analysis can be employed for prediction and overlaps
with the field of machine learning (a branch of artificial
intelligence that employs algorithms to identify patterns in data
and/or make predictions based on evaluated data).
[0034] Different models can be employed in regression analysis to
model the relationship between two variables. Linear regression is
a type of regression analysis. Linear regression models the
relationship between a dependent variable (e.g., pH level) and an
independent variable (e.g., information indicating general health
of the wearer of the contact lens) using linear predictor
functions. Unknown model parameters are estimated from the data on
which linear regression is performed. Interpolation methods can be
employed to perform prediction based on values within the set of
collected data used for model-fitting while extrapolation can be
employed to perform prediction based on values outside the set of
collected data.
[0035] In linear regression models, the conditional mean of an
independent variable given the dependent variable value is
typically an affine function. In some cases, the median, or some
other quantile of the conditional distribution of the independent
variable given the dependent variable is a linear function of the
dependent variable.
[0036] Non-linear regression is a type of regression analysis in
which observed information (e.g., glucose concentration value) is
modeled by a non-linear function. The non-linear function is a
combination of the model parameters and depends on an independent
variable.
[0037] Apparatus, systems and methods disclosed herein relate to
contact lenses that facilitate collection and/or processing of
information. The contact lens collects information from the body of
the wearer of the contact lens (via sensors) and an analysis
component performs statistical analysis on the collected
information. An external device can power the sensors on the
contact lens and can receive inputs from the wearer of the contact
lens about general health feelings (e.g., whether the wearer of the
contact lens is lethargic or energetic). Predictions and
recommendations can be made by the analysis component based on the
statistical analysis performed.
[0038] One or more of the aspects described herein can
advantageously facilitate non-invasive monitoring of various body
features and associated analysis, predictions and recommendations
for optimal health management.
[0039] In one particular aspect, an analysis component is provided.
The analysis component can include: a memory configured to store
computer executable components; and a processor configured to
execute the following computer executable components stored in the
memory: a communication component configured to receive, from a
contact lens, information indicative of features sensed on the
contact lens, wherein the features sensed are features of a wearer
of the contact lens; and a statistical analysis component
configured to generate statistical information based, at least, on
the information indicative of features sensed on the contact
lens.
[0040] In an aspect, a contact lens is provided. The contact lens
can include: a substrate; and a circuit. The circuit can include: a
plurality of sensors configured to sense respective features
associated with a wearer of the contact lens, wherein the plurality
of sensors are configured to be powered by a portable radio
frequency (RF) device external to the contact lens; and a
communication component configured to transmit, to the RF device,
at least, one of information indicative of sensed features or a
recommendation based on the information indicative of sensed
features.
[0041] In an aspect, a method is provided. The method can include:
receiving power, at a plurality of sensors on a contact lens, from
a device external to the contact lens; sensing, via the plurality
of sensors, a respective plurality of features associated with a
wearer of the contact lens; and transmitting, from the contact
lens, information indicative of sensed features, to an analysis
component configured to perform statistical analysis on the
information indicative of sensed features.
[0042] In an aspect, a system is provided. The system can include a
contact lens and an analysis component. The contact lens can
include: a substrate; and a circuit, disposed on or within the
substrate. The circuit can include: a plurality of sensors
configured to sense respective features associated with a wearer of
the contact lens; and a communication component configured to
communicate information indicative of sensed features. The analysis
component can be external to the contact lens. The analysis
component can be configured to: receive the information indicative
of sensed features; and generate statistical information based, at
least, on the information indicative of sensed features.
[0043] Various aspects will now be discussed with reference to the
figures. Turning first to FIG. 1, system 100 includes a contact
lens 102 that covers at least a portion of eye 104. The contact
lens 102 can be configured to sense a plurality of features of the
wearer of the contact lens 102 and facilitate generation of
corresponding statistical information 130, an analysis component
132 that can receive sensed information 120 from the contact lens
102 and generate statistical information 130 and/or a radio
frequency (RF) reader 116 to which information 120 or statistical
information 130 can be transmitted.
[0044] In some aspects, the system 100 can also include a device
118 configured to store information 120 sensed on the contact lens
102 and/or statistical information 130 generated by the analysis
component 132. The device 118 can also perform various different
primary functions (e.g., a smart phone, laptop or head-mounted
display device that performs communication, word processing and/or
display functions in addition to storage of information 120 or
statistical information 130). While the analysis component 132 is
shown as a separate component from the device 118, in some aspects,
the analysis component 132 can be included in the device 118. In
some aspects, the analysis component 132 can be included in the
contact lens 102.
[0045] The contact lens 102 can include a substrate 114, sensors
106, 108, 110, 112, sensor circuitry 128 and communication
component 122. In some aspects, the contact lens 102 can also
include memory 124 and/or microprocessor 126. In some aspects, one
or more of the sensors 106, 108, 110, 112, analysis component 132,
communication component 122, memory 124 and/or microprocessor 126
can be included as part of one or more circuits on the contact lens
102. In some aspects, one or more of sensors 106, 108, 110, 112,
communication component 122, memory 124 and/or microprocessor 126
can be communicatively and/or electrically coupled to one another
to perform one or more functions of the contact lens 102. The
components can be disposed on or within substrate 114.
[0046] The sensors 106, 108, 110, 112 can be configured to sense
various features associated with a wearer of the contact lens 102.
For example, sensor 106 can be configured to sense glucose
information (e.g., glucose concentration and/or glucose level)
associated with the wearer of the contact lens 102. Sensor 108 can
be configured to sense cholesterol information (e.g., cholesterol
level) associated with the wearer of the contact lens 102. Sensor
110 can be configured to sense pH level associated with the wearer
of the contact lens 102. Sensor 112 can be configured to sense
temperature associated with the wearer of the contact lens 102.
[0047] Glucose sensor 106 and cholesterol sensor 108 can be
amperometric electrochemical sensors that detect the presence
and/or concentration of glucose and cholesterol, respectively. The
sensors 106, 108 can employ an oxidases enzyme to catalyze the
oxidation of glucose and cholesterol by oxygen. The product can be
hydrogen peroxide (H.sub.2O.sub.2). For example, glucose oxidase
can be deposited onto the sensor 106 to enable the sensor 106 to
perform as a glucose biosensor. Similarly, cholesterol oxidase can
be deposited onto the sensor 108 to enable the sensor 108 to
perform as a cholesterol biosensor. When glucose or cholesterol is
sensed at sensors 106, 108, current can flow and the output current
can be indicative of the level of glucose sensed by sensor 106 or
the level of cholesterol sensed by sensor 108. The sensor circuitry
128 can be coupled to the sensors 106, 108 and determine the output
current for the sensors 106, 108. The output current can be
indicative of the concentration of the analyte in the solution.
[0048] Sensor 110 can be an electrochemical sensor that has a
voltage output indicative of the pH level in tear fluid incident on
the contact lens 102. In some aspects, the sensor 110 includes at
least a measuring electrode, a reference electrode and a
temperature sensing component. The measuring electrode can develop
a potential as a function of the hydrogen ion concentration in the
solution being sensed. The potential can be measured relative to
the potential at the reference electrode. Because the potential at
the measuring circuit can also change based on temperature changes,
the potential at the measuring circuit can be adjusted based on the
temperature (which is sensed by the temperature sensing component).
The adjusted potential is a function of the pH level in the
solution sensed. The sensor circuitry 128 can be coupled to the
sensor 110 and determine the change in potential.
[0049] Sensor 112 can be a temperature sensor that changes
resistance based on sensed temperature. For example, the sensing
component of sensor 112 can include a resistance component (e.g.,
resistance thermometer) configured to sense temperature on the
contact lens 102 and increase resistance with a rise in temperature
or decrease resistance with a decrease in temperature. Current
output from the sensor 112 can change as a result of the change in
the resistance. As such, the output current can be indicative of
the temperature (or change in temperature) sensed by sensor 112.
The sensor circuitry 128 can be coupled to the sensor 110 and
determine the output current.
[0050] The memory 124 can store information regarding cholesterol,
glucose, temperature and/or pH levels/concentrations
measured/sensed and/or computer-executable instructions for
execution by the microprocessor 126. FIG. 2 is an illustration of
an exemplary non-limiting data storage of a contact lens that
facilitates collection and/or processing of information in
accordance with aspects described herein. FIG. 3 is an illustration
of an exemplary non-limiting table of information stored in a
contact lens in accordance with aspects described herein. Memory
124 can include data storage 200 in some aspects.
[0051] With reference to FIGS. 2 and 3, in some aspects, a data
storage (e.g., data storage 200) can be provided on the contact
lens 102 and can store the information sensed by the sensors 106,
108, 110, 112. For example, the data storage 200 can be included as
part of the memory 124 in some aspects. In some aspects, data
storage 200 is not provided on the contact lens 102, but is
accessible by the contact lens 102 for storage of and retrieval of
information 120 and/or statistical information 130.
[0052] Data storage 200 can store glucose information 204 (e.g.,
glucose concentrations and/or information indicative of the level
of the glucose concentration), cholesterol information 202 (e.g.,
cholesterol concentration and/or information indicative of the
level of the cholesterol concentration), pH level information 206
(e.g., numerical pH value and/or information indicative of the
level of the pH) and/or temperature information 208 (e.g.,
temperature value and/or information indicative of the level of the
temperature).
[0053] As shown in table 300 of FIG. 3, the numerical values
associated with concentrations or levels can be stored in data
storage 200 as glucose information 204 (e.g., glucose
concentrations and/or information indicative of the level of the
glucose concentration), cholesterol information 202 (e.g.,
cholesterol concentration and/or information indicative of the
level of the cholesterol concentration), pH level information 206
(e.g., numerical pH value and/or information indicative of the
level of the pH) and/or temperature information 208 (e.g.,
temperature value and/or information indicative of the level of the
temperature). The measured/sensed received cholesterol information
202, glucose information 204, temperature information 208 and/or pH
level information 206 can be current information and/or past
information. In some aspects, the information can be collected over
a period of time. For example, the measured/sensed received
cholesterol information 202, glucose information 204, temperature
information 208 and/or pH level information 206 can be collected
over a period of time (e.g., one month, six months, one week) prior
to the analysis component 132 performing statistical analysis on
the measured/sensed information.
[0054] The data storage 200 can be configured to store information
transmitted to, received by and/or processed by the analysis
component 132. For example, the data storage 200 can store glucose
information 204 (e.g., current, historical and/or average glucose
concentration information), cholesterol information 202 (e.g.,
current, historical and/or average cholesterol levels), pH level
information 206 (e.g., current, historical and/or average pH
levels) and/or temperature information 208 (e.g., current,
historical and/or average body temperature information). In some
aspects, although not shown, the data storage 200 can store
statistical information (e.g., statistical information 130)
received from the analysis component 132.
[0055] The values and the levels provided are merely exemplary for
the purposes of illustrating the systems and methods herein and may
or may not be accurate depictions of the true values,
concentrations and/or levels by which the system and/or the methods
operate.
[0056] The microprocessor 126 can execute computer-executable
instructions to perform one or more functions of the contact lens
102. For example, in some aspects, the microprocessor 126 can
convert the output current from various sensors 106, 108, 110, 112
to measured/sensed concentrations and/or levels.
[0057] In various aspects, sensors 106, 108, 110, 112 can sense
various features concurrently, at non-overlapping times or at
random. For example, in some aspects, the sensors 106, 108, 110,
112 can perform sensing on a single sample of fluid incident on the
contact lens 102 and thereby perform sensing concurrently.
[0058] In some aspects, the sensors 106, 108, 110, 112 are remotely
powered for short time intervals by device 118. For example,
communication component 122 can include a radio frequency (RF)
antenna (not shown) that can receive RF signals from device 118 for
powering the sensors 106, 108, 110, 112 and sensor circuitry
128.
[0059] The RF signals received can enable the sensors 106, 108,
110, 112 and sensor circuitry 128 to be powered on for relatively
short periods of time (e.g., 10 seconds, 20 seconds, 1 minute).
When the communication component 122 receives the RF signal and the
sensors 106, 108, 110, 112 and sensor circuitry 128 are powered on,
the sensors 106, 108, 110, 112 can read/sense glucose, cholesterol,
temperature and/or pH in the wearer of the contact lens 102, and
the sensor circuitry 128 can determine various information 120
(e.g., concentrations and/or levels of the glucose, cholesterol,
temperature and/or pH).
[0060] In some aspects, the communication component 122 can
transmit the information 120 to a device external to the contact
lens 102. For example, the communication component 122 can transmit
the information 120 to device 118 for storage of the information
120. As another example, the communication component 122 can
transmit the information 120 to analysis component 132 or RF reader
116.
[0061] It is to be appreciated that in accordance with one or more
aspects described in this disclosure, users can opt-in or opt-out
of providing personal information, demographic information,
location information, proprietary information, sensitive
information, or the like in connection with data gathering aspects.
Moreover, one or more aspects described herein can provide for
anonymizing collected, received or transmitted data.
[0062] In various aspects, device 118 can include any number of
devices external to the contact lens 102 and able to communicate RF
signals and receive inputs from a wearer of the contact lens 102.
By way of example, but not limitation, device 118 can include a
smart phone, tablet computer, laptop, head-mounted display device,
wingman device and/or RF reader (e.g., RF reader 116).
[0063] The analysis component 132 of system 100 can be described in
greater detail with reference to FIGS. 1-5. FIG. 4 is an
illustration of an exemplary non-limiting diagram of an analysis
component that facilitates processing of information in accordance
with aspects described herein. FIG. 5 is an illustration of an
exemplary non-limiting graph detailing statistical information
generated by an analysis component in accordance with aspects
described herein.
[0064] Turning first to FIG. 4, the analysis component 132 can
include a concentration/level comparison component 402, a
statistical analysis component 404, memory 410, microprocessor 414
and/or communication component 416. The concentration/level
comparison component 402, statistical analysis component 404,
memory 410, microprocessor 414 and/or communication component 416
can be communicatively or electrically coupled to one another to
perform one or more functions of the analysis component 132.
[0065] The communication component 416 can be configured to
wirelessly receive information 120 sensed by the sensors 106, 108,
110, 112 at contact lens 102. For example, with reference to FIGS.
2 and 3, the communication component 416 can received cholesterol
information 202, glucose information 204, temperature information
208 and/or pH level information 206 measured by sensors 106, 108,
110, 112 and transmitted from contact lens 102.
[0066] The memory 410 can store received cholesterol information
202, glucose information 204, temperature information 208 and/or pH
level information 206 and/or computer-executable instructions for
execution by the microprocessor 414. The microprocessor 414 can
execute computer-executable instructions to perform one or more
functions of the analysis component 132. For example, in some
aspects, the microprocessor 414 can facilitate statistical analysis
performed by the analysis component 132.
[0067] The concentration/level comparison component 402 can compare
received cholesterol information 202, glucose information 204,
temperature information 208 and/or pH level information 206 with
biological features information stored at data storage 412. In some
aspects, the biological features information can include tables,
charts and/or graphs detailing various constants/values for
cholesterol, glucose, temperature and/or pH level for adults or
customized for the wearer of the contact lens 102. The biological
features information can also include information corresponding to
the different values indicating whether a value/level is too high,
too low or optimal.
[0068] In various aspects, the concentration/level comparison
component 402 can determine whether the measured/sensed
concentration or level is too high, too low or optimal based on the
comparison between the received cholesterol information 202,
glucose information 204, temperature information 208 and/or pH
level information 206 and the biological features information
stored at data storage 412. In some aspects, the
concentration/level comparison component 402 can determine
variation over time in an amount of one or more of the features in
a body of the wearer of the contact lens.
[0069] In various aspects, the statistical analysis component 404
can perform any number of different types of mathematical functions
for processing and/or statistical analysis of the received
cholesterol information 202, glucose information 204, temperature
information 208 and/or pH level information 206. In some aspects,
the statistical analysis component 404 can access equations stored
at the data storage 412 to perform such functions. By way of
example, but not limitation, the statistical analysis component 404
can perform averaging, computation of probabilities and probability
distribution functions, cumulative distribution functions,
calculation of series, vector analysis, determination of percentile
information or measures of variation associated with the
measured/sensed information and any number of other types of
mathematical operations associated with or used during statistical
analysis. The generated information can be statistical information
130.
[0070] The statistical analysis component 404 can also include a
regression analysis component 406. The regression analysis
component 406 can receive cholesterol information 202, glucose
information 204, temperature information 208 and/or pH level
information 206 sensed by sensors 106, 108, 110, 112. The
cholesterol information 202, glucose information 204, temperature
information 208 and/or pH level information 206 (including
associated qualitative or quantitative information) can considered
dependent variables by the regression analysis component 406.
[0071] The regression analysis component 406 can also receive
general health information descriptive of how the wearer of the
contact lens 102 is feeling. For example, the wearer of the contact
lens 102 can enter information at the device 118 regarding whether
the wearer of the contact lens 102 is experiencing any sickness
and/or the general feeling/mood of the wearer of the contact lens
102. For example, information indicative of energy level, double
vision, pain, appetite can be optional information input as general
health information. The information can considered independent
variables by the regression analysis component 406.
[0072] The general health information can be input via voice
commands/information, keyboard or touch screen input or any number
of other ways that information can be input into device 118.
[0073] In various aspects, the general health information can be
transmitted from the device 118 to the analysis component 132
(and/or to the contact lens 102, which can transmit the general
health information to the analysis component 132). The analysis
component 132 can store the information as general health
information at the data storage 412 in some aspects.
[0074] The regression analysis component 406 can employ regression
analysis to relate the measured/sensed received cholesterol
information 202, glucose information 204, temperature information
208 and/or pH level information 206 to one of the variables entered
by the wearer of the contact lens 102 as general health information
(while, in some aspects, holding constant any other variables
entered by the wearer of the contact lens 102). The regression
analysis component 406 can perform regression analysis to identify
the best models (e.g., linear models, non-linear models) to relate
the measured/sensed information to the general health information
input by the wearer of the contact lens 102. The regression
analysis component 406 can then employ the model to predict health
of the wearer of the contact lens 102.
[0075] For example, in some aspects, the regression analysis
component 406 can evaluate the measured sensed received cholesterol
information 202, glucose information 204, temperature information
208 and/or pH level information 206 and the general health
information and apply a linear model to the variables to relate the
sensed information to the general health information as described
and shown with reference to FIG. 5.
[0076] Turning to FIG. 5, measured/sensed cholesterol levels can be
associated with the input general health information associated
with energy level of the wearer of the contact lens. The level of
lethargy can be related to the measured/sensed cholesterol levels
for a prediction of future health condition. As shown, the total
cholesterol level of 100 was measured/sensed when the wearer of the
contact lens reported a very energetic general health feeling. When
the total cholesterol level increased beyond 200, the general
health feeling reported by the wearer of the contact lens was
lethargic. Further, increasingly high total cholesterol values over
200 corresponded to general health feelings of greater lethargy. As
described herein, in a normal human adult, a total cholesterol
level of less than 200 is optimal.
[0077] The regression analysis component 406 can determine a model
to relate the total cholesterol level to the general health feeling
and perform predictions about impending health condition and/or
recommendations regarding health maintenance. For example, based on
the example shown in FIG. 5, while general optimum levels are any
total cholesterol levels below 200, the regression analysis
component 406 can recommend that the wearer of the contact lens 102
maintain cholesterol levels close to 150 for maximum energy
levels.
[0078] In some aspects, the statistical analysis component 404 can
perform data mining operations for pattern recognition of the
values associated with received cholesterol information 202,
glucose information 204, temperature information 208 and/or pH
level information 206. For example, the statistical analysis
component 404 can analyze large quantities of numerical values
associated with received cholesterol information 202, glucose
information 204, temperature information 208 and/or pH level
information 206. The statistical analysis component 404 can then
perform cluster analysis by identifying similar measured/sensed
values and grouping the similar values together. The statistical
analysis component 404 can also perform anomaly detection to
identify outliers in the group of values.
[0079] The regression analysis component 406 can employ pattern
information to determine whether particular patterns of values for
cholesterol, glucose, temperature and/or pH occur at particular
times of day, month, for example. Cluster analysis can be employed
to determine general health information that tends to be associated
with particular measured/sensed values while anomaly detection can
be employed to determine peculiarities in the body response (e.g.,
measured/sensed values that are significantly different from other
measured/sensed values measured when the same/similar general
health condition was noted).
[0080] As another example, in aspects wherein the wearer of the
contact lens inputs information indicative of the type of food that
the wearer of the contact lens 102 is eating or has eaten, the
regression analysis component 406 can employ regression analysis to
determine whether particular patterns of values for cholesterol,
glucose, temperature and/or pH result after eating particular types
of food.
[0081] The time interval between statistical analysis calculations
can be static or dynamically changed. For example, if the analysis
component 132 determines that the measured/sensed information
indicates abnormal levels, the communication component 416 can
transmit information to the contact lens 102 to update the
frequency during which the contact lens 102 transmits stored
information to the analysis component 132. As another example, the
time interval can be pre-programmed prior to the initial use of the
contact lens 102. For example, the wearer of the contact lens 102
and/or the medical provider for the wearer of the contact lens 102
can determine the time intervals between statistical analysis
calculations.
[0082] In some aspects, a delay of several (e.g., 3) days may pass
before the manifestation of symptoms predicted by the statistical
analysis component 404. Accordingly, preventative measures and
treatment can be preemptively provided.
[0083] In various aspects, the analysis component 132 can generate
the statistical information 130 in real-time. For example, the
statistical information 130 can be generated by the analysis
component 132 as the sensors 106, 108, 110, 112 sense the features
of the wearer of the contact lens 102 (and the contact lens 102
transmits the information 120 to the analysis component 132).
[0084] In other aspects, the sensors 106, 108, 110, 112 can perform
sensing upon powering up (when RF signals are received at the
contact lens 102), and the sensor circuitry 128 can determine the
levels of the information 120 sensed by the sensors 106, 108, 110,
112. The information 120 sensed can be later stored (e.g., at the
data storage 412 of the memory 410) and the analysis component 132
can perform statistical analysis on the stored information 120.
[0085] Turning back to FIG. 1, in some aspects, the communication
component 122 of contact lens 102 can transmit information to the
device 118 based on the information 120 sensed by the sensors 106,
108, 110, 112. For example, the communication component 122 can
transmit information identifying nearby stores that sell foods high
in sugar content (e.g., bakeries) if the sensor that measures
glucose (e.g., sensor 106) measures/senses a low glucose level.
Similarly, the communication component 122 can transmit information
identifying nearby hospitals or clinics if the sensors 106, 108,
110, 112 measure severely abnormal glucose, cholesterol, pH and/or
temperature levels.
[0086] In some aspects, the communication component 122 of contact
lens 102 can receive statistical information 130 from the analysis
component 132. The statistical information 130 can include, but is
not limited to, a prediction or forecast regarding impending
symptoms or medical condition, recommendations regarding
nutritional intake, recommendation to schedule an appointment with
a medical provider and/or identification of stores that can provide
dietary choices suitable for the needs of the wearer of the contact
lens 102.
[0087] FIGS. 6 and 7 are illustrations of exemplary non-limiting
flow diagrams of methods for a contact lens that facilitates
collection and/or processing of information in accordance with
aspects described herein. Turning first to FIG. 6, at 602, method
600 can include receiving power at a plurality of sensors on a
contact lens from a device, wherein the device is external to the
contact lens (e.g., using the sensors 106, 108, 110, 112). In
various embodiments, the power can be received from a smart phone,
head-mounted display device, laptop, wingman device associated with
the wearer of the contact lens. In various aspects, the sensors can
be powered intermittently upon receipt of limited bursts of
power.
[0088] At 604, method 600 can include sensing, via a plurality of
sensors disposed on or within a substrate of the contact lens, a
respective plurality of features associated with a wearer of the
contact lens (e.g., using the sensors 106, 108, 110, 112). In
various aspects, the sensing can be performed while the sensors are
intermittently powered. Different sensors can sense different
features of the wearer of the contact lens. For example, different
sensors can measure/sense glucose, cholesterol, temperature and/or
pH level and/or concentration.
[0089] At 606, method 600 can include transmitting, from the
contact lens, information indicative of the sensed features (e.g.,
using the communication component 122). The transmission can be to
an analysis component configured to perform statistical analysis of
the information. In various aspects, statistical analysis can
include regression analysis employing the information indicative of
sensed features, information about general health feelings,
predictions or inferences associated with a health condition of the
wearer of the contact lens, determining average values,
percentages, measures of variation associated with the sensed
features and the like.
[0090] Turning now to FIG. 7, at 702, method 700 can include
sensing, via a plurality of sensors on a contact lens, respective
features associated with a wearer of the contact lens, wherein the
sensors are configured to be powered by a portable RF device
external to the contact lens (e.g., using the sensors 106, 108,
110, 112). The sensors can be powered by various different types of
RF devices including, but not limited to, smart phones,
head-mounted display devices, laptops or the like. The device can
be configured to power the sensors for limited time intervals. The
sensors can then perform sensing during the time intervals during
which they are powered by the device.
[0091] At 704, method 700 can include transmitting, to the RF
device, at least one of information indicative of the sensed
features or a recommendation based on the information indicative of
the sensed features (e.g., using the communication component 122).
For example, the contact lens can transmit to the RF device values
such as cholesterol or glucose level/concentration, pH level and/or
temperature level. In various aspects, the RF device can be
associated with the wearer of the contact lens. As such, the wearer
of the contact lens can be apprised of his/her body condition.
[0092] The recommendation can be an identification of dietary
options (e.g., stores, bakeries, restaurants serving food that may
address a deficiency or other problem determined based on the
sensed features). For example, the name and location of a nearby
bakery can be provided as a recommendation if a low glucose level
is determined to exist for the wearer of the contact lens. As
another example, the recommendation can be an identification of
healthcare information (e.g., nearby hospitals, clinics, contact
information for internal medicine physician or other specialists)
for the wearer of the contact lens.
[0093] In some aspects, the recommendation that the contact lens
can transmit to the RF device for viewing by the wearer of the
contact lens can be received from an analysis component configured
to perform statistical analysis on the sensed information and
generate the recommendation as a result of the statistical
analysis. Accordingly, sensing can be performed on the contact lens
and statistical analysis can be performed by an analysis component
external to the contact lens. Upon receipt of the statistical
information at the contact lens, the contact lens can provide the
information to the RF device.
[0094] While the aspects described herein detail the component that
performs statistical analysis and the RF device as separate, in
some aspects, the analysis component and the RF device can be the
same component (or the analysis component can be included on the
contact lens).
Exemplary Networked and Distributed Environments
[0095] FIG. 8 provides a schematic diagram of an exemplary
networked or distributed computing environment with which one or
more aspects described in this disclosure can be associated. The
distributed computing environment includes computing objects 810,
812, etc. and computing objects or devices 820, 822, 824, 826, 828,
etc., which can include programs, methods, data stores,
programmable logic, etc., as represented by applications 830, 832,
834, 836, 838. It can be appreciated that computing objects 810,
812, etc. and computing objects or devices 820, 822, 824, 826, 828,
etc. can include different devices, such as active contact lenses
(and components thereof), personal digital assistants (PDAs),
audio/video devices, mobile phones, MPEG-1 Audio Layer 3 (MP3)
players, personal computers, laptops, tablets, etc.
[0096] Each computing object 810, 812, etc. and computing objects
or devices 820, 822, 824, 826, 828, etc. can communicate with one
or more other computing objects 810, 812, etc. and computing
objects or devices 820, 822, 824, 826, 828, etc. by way of the
communications network 840, either directly or indirectly. Even
though illustrated as a single element in FIG. 8, network 840 can
include other computing objects and computing devices that provide
services to the system of FIG. 8, and/or can represent multiple
interconnected networks, which are not shown.
[0097] In a network environment in which the communications
network/bus 840 can be the Internet, the computing objects 810,
812, etc. can be Web servers, file servers, media servers, etc.
with which the client computing objects or devices 820, 822, 824,
826, 828, etc. communicate via any of a number of known protocols,
such as the hypertext transfer protocol (HTTP).
Exemplary Computing Device
[0098] As mentioned, advantageously, the techniques described in
this disclosure can be associated with any suitable device. In
various aspects, the data store can include or be included within,
any of the memory described herein and/or any of the contact lenses
described herein. In various aspects, the data store can be any
repository for storing information transmitted to or received from
the contact lens.
[0099] FIG. 9 illustrates an example of a suitable computing system
environment 900 in which one or aspects of the aspects described in
this disclosure can be implemented. Components of computer 910 can
include, but are not limited to, a processing unit 920, a system
memory 930, and a system bus 922 that couples various system
components including the system memory to the processing unit
920.
[0100] Computer 910 typically includes a variety of computer
readable media and can be any available media that can be accessed
by computer 910. The system memory 930 can include computer storage
media in the form of volatile and/or nonvolatile memory such as
read only memory (ROM) and/or random access memory (RAM). By way of
example, and not limitation, memory 930 can also include an
operating system, application programs, other program components,
and program data.
[0101] A user can enter commands and information into the computer
910 through input devices 940 (e.g., keyboard, keypad, a pointing
device, a mouse, stylus, touchpad, touch screen, motion detector,
camera, microphone or any other device that allows the user to
interact with the computer 910). A monitor or other type of display
device can be also connected to the system bus 922 via an
interface, such as output interface 950. In addition to a monitor,
computers can also include other peripheral output devices such as
speakers and a printer, which can be connected through output
interface 950.
[0102] The computer 910 can operate in a networked or distributed
environment using logical connections to one or more other remote
computers, such as remote computer 980. The remote computer 980 can
be a personal computer, a server, a router, a network PC, a peer
device or other common network node, or any other remote media
consumption or transmission device, and can include any or all of
the elements described above relative to the computer 910. The
logical connections depicted in FIG. 9 include a network 982, such
local area network (LAN) or a wide area network (WAN), but can also
include other networks/buses e.g., cellular networks.
[0103] Computing devices typically include a variety of media,
which can include computer-readable storage media and/or
communications media, in which these two terms are used herein
differently from one another as follows. Computer-readable storage
media can be any available storage media that can be accessed by
the computer, can be typically of a non-transitory nature, and can
include both volatile and nonvolatile media, removable and
non-removable media. By way of example, and not limitation,
computer-readable storage media can be implemented in connection
with any method or technology for storage of information such as
computer-readable instructions, program components, structured
data, or unstructured data. Computer-readable storage media can
include, but are not limited to, RAM, ROM, electrically erasable
programmable read only memory (EEPROM), flash memory or other
memory technology, or other tangible and/or non-transitory media
which can be used to store desired information. Computer-readable
storage media can be accessed by one or more local or remote
computing devices, e.g., via access requests, queries or other data
retrieval protocols, for a variety of operations with respect to
the information stored by the medium. In various aspects, the
computer-readable storage media can be, or be included within, the
memory, contact lens (or components thereof) or reader described
herein.
[0104] On the other hand, communications media typically embody
computer-readable instructions, data structures, program components
or other structured or unstructured data in a data signal such as a
modulated data signal, e.g., a carrier wave or other transport
mechanism, and includes any information delivery or transport
media. The term "modulated data signal" or signals refers to a
signal that has one or more of its characteristics set or changed
in such a manner as to encode information in one or more
signals.
[0105] It is to be understood that the aspects described in this
disclosure can be implemented in hardware, software, firmware,
middleware, microcode, or any combination thereof. For a hardware
aspect, the processing units can be implemented within one or more
application specific integrated circuits (ASICs), digital signal
processors (DSPs), digital signal processing devices (DSPDs),
programmable logic devices (PLDs), field programmable gate arrays
(FPGAs), processors, controllers, micro-controllers,
microprocessors and/or other electronic units designed to perform
the functions described in this disclosure, or a combination
thereof.
[0106] For a software aspect, the techniques described in this
disclosure can be implemented with components or components (e.g.,
procedures, functions, and so on) that perform the functions
described in this disclosure. The software codes can be stored in
memory units and executed by processors.
[0107] What has been described above includes examples of one or
more aspects. It is, of course, not possible to describe every
conceivable combination of components or methodologies for purposes
of describing the aforementioned aspects, but one of ordinary skill
in the art can recognize that many further combinations and
permutations of various aspects are possible. Accordingly, the
described aspects are intended to embrace all such alterations,
modifications and variations that fall within the spirit and scope
of the appended claims.
[0108] Moreover, the term "or" is intended to mean an inclusive
"or" rather than an exclusive "or." That is, unless specified
otherwise, or clear from the context, the phrase "X employs A or B"
is intended to mean any of the natural inclusive permutations. That
is, the phrase "X employs A or B" is satisfied by any of the
following instances: X employs A; X employs B; or X employs both A
and B. In addition, the articles "a" and "an" as used in this
application and the appended claims should generally be construed
to mean "one or more" unless specified otherwise or clear from the
context to be directed to a singular form.
[0109] The aforementioned systems have been described with respect
to interaction between several components. It can be appreciated
that such systems and components can include those components or
specified sub-components. Sub-components can also be implemented as
components communicatively coupled to other components rather than
included within parent components (hierarchical). Additionally, it
is to be noted that one or more components can be combined into a
single component providing aggregate functionality. Any components
described in this disclosure can also interact with one or more
other components not specifically described in this disclosure but
generally known by those of skill in the art.
[0110] In view of the exemplary systems described above
methodologies that can be implemented in accordance with the
described subject matter will be better appreciated with reference
to the flowcharts of the various figures. While for purposes of
simplicity of explanation, the methodologies are shown and
described as a series of blocks, it is to be understood and
appreciated that the claimed subject matter is not limited by the
order of the blocks, as some blocks can occur in different orders
and/or concurrently with other blocks from what is depicted and
described in this disclosure. Where non-sequential, or branched,
flow is illustrated via flowchart, it can be appreciated that
various other branches, flow paths, and orders of the blocks, can
be implemented which achieve the same or a similar result.
Moreover, not all illustrated blocks may be required to implement
the methodologies described in this disclosure after.
[0111] In addition to the various aspects described in this
disclosure, it is to be understood that other similar aspects can
be used or modifications and additions can be made to the described
aspect(s) for performing the same or equivalent function of the
corresponding aspect(s) without deviating there from. Still
further, multiple processing chips or multiple devices can share
the performance of one or more functions described in this
disclosure, and similarly, storage can be provided across a
plurality of devices. The invention is not to be limited to any
single aspect, but rather can be construed in breadth, spirit and
scope in accordance with the appended claims.
* * * * *