Baselining user profiles from portable device information

• US 10,368,744 B1
• Filed: 12/28/2015
• Issued: 08/06/2019
• Est. Priority Date: 02/17/2015
• Status: Active Grant

• Current Assignee: HALO Wearables LLC
• Original Assignee: HALO Wearables LLC
• Inventors: Miller, Devin Warner, Miller, David Rich
• Primary Examiner(s): Tran, Michael T
• Application Number:
  US14/981,246
• Time in Patent Office: 1,317 Days
• Field of Search: 706 11, 700 92
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0537 Measuring body composition by impedance, e.g. tissue hydration or fat content
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/4266 sweat secretion
• CPC Class Codes: A61B 5/443 Evaluating skin constituents, e.g. elastin, melanin, water
• CPC Class Codes: A61B 5/4875 Hydration status, fluid retention of the body
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/746 : Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: G06F 1/163 : Wearable computers, e.g. on a belt
• CPC Class Codes: G06N 7/01 : Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: H04B 1/385 : Transceivers carried on the body, e.g. in helmets
• CPC Class Codes: H04B 2001/3855 : carried in a belt or harness
• CPC Class Codes: H04B 2001/3861 : carried in a hand or on fingers

Abstract

A system includes a memory device for computer storage and a processing device to: receive, and store in the memory device as a user profile, profile information for a user, wherein the profile information comprises any or a combination of: gender, age, weight, health and fitness level. The processing device further identifies, from a plurality of baselines profiles, a baseline profile that is most-similar to the user profile based on a correlation between the user profile information and baseline profile information. The processing device further sets a baseline for measurements of a physiological parameter of the user corresponding to levels of the physiological parameter of an individual with the baseline profile that is most-similar.

Claims

1. A system comprising:

a first memory device for computer storage;

a processing device coupled to the first memory device, wherein the processing device is configured to;

receive, from an input device, profile information for a user, wherein the profile information comprises at least one of;

gender information, age information, weight information, health information, or fitness level information;

store the profile information at the first memory device;

generate a user profile based on the profile information;

query a plurality of baseline profiles stored at the first memory device or a second memory device to identify a subset of baseline profiles from among the plurality of baseline profiles, wherein;

the plurality of baseline profiles are at least one of profiles for other individuals or default profiles; and

the subset of baseline profiles comprises;

a first baseline profile that is a most-similar to the user profile based on a first correlation between the profile information of the user and baseline profile information of the first baseline profile;

a second baseline profile that is a second most-similar to the user profile based on a second correlation between the profile information of the user and baseline profile information of the second baseline profile;

aggregate the baseline profile information from the first baseline profile and the baseline profile information from the second baseline profile to obtain an aggregated baseline profile; and

set a baseline for a physiological parameter of the user from which to measure against for the physiological parameter, wherein the baseline is based on the physiological parameter of the aggregated baseline profile.

2. The system of claim 1, wherein the processing device further to communicate the baseline to a wearable device of the user.

3. The system of claim 1, further comprising a communication interface to:

send the profile information and the baseline for the user to a networked device over a network, for storage in the networked device;

send any updates to the user profile to the networked device;

receive, from the networked device, a new baseline from among the plurality of baseline profiles based on the updates to the user profile; and

set a new baseline for the user based on the new baseline profile.

4. The system of claim 1, wherein the processing device is further to:

retrieve research information related to the physiological parameter;

correlate the research information with measurements of the physiological parameter of the user to generate a research correlation; and

adjust the baseline for the user related to the physiological parameter in response to the research correlation.

5. The system of claim 1, wherein the processing device is further to:

receive measurements of the physiological parameter for the user; and

update the baseline in response to receipt of recently received measurements of the physiological parameter.

6. The system of claim 1, wherein, to identify the subset of baseline profiles, the processing device to:

apply weights to a plurality of traits within the profile information, to generate a plurality of weighted traits; and

match the weighted traits with corresponding levels of the weighted traits within the plurality of baseline profiles.

7. The system of claim 1, wherein the processing device is further to set the baseline for the physiological parameter as an average of levels of the physiological parameter of the subset of baseline profiles.

8. The system of claim 1, further comprising a housing formed and shaped to affix to the user, wherein a sensor is integrated into the housing such as to make contact with a body of the user, the sensor configured to obtain physiological measurements.

9. The system of claim 1, wherein the profile information further includes family health medical records.

22. The system of claim 1, wherein:

the baseline profiles of the first subset of the baseline profiles or the second subset of the baseline profiles each include data indicative of a characteristic of another individual; and

the processing device is configured to average the data of the baseline profiles of the first subset of the baseline profiles or the second subset of the baseline profiles to obtain the aggregated baseline profile.

10. A processing device comprising non-transitory memory for storage of data and instructions, that when executed, cause the processing device to:

receive a first set of profile data from a user interface for a first user at a first point in time, wherein;

the first set of profile data comprises at least one of;

weight information, health information, or fitness level information; and

the first set of profile data is indicative of information for the first user over a first period of time;

dynamically weight data of the first set of profile data for the first user based on a change of the first set of profile data over time, wherein the change of the first set of profile data over time is indicative of one or more characteristics of the first user changing over time;

generate a user profile for the first user based on the weighted data of the first set of profile data;

identify a plurality of baseline profiles stored at the non-transitory memory or another non-transitory memory;

match the user profile to a first most-similar baseline profile from among the plurality of baseline profiles at the first point in time;

set a baseline for measurements of a physiological parameter of the first user based on the first most-similar baseline profile;

receive a second set of profile data from the user interface for the first user at a second point in time, wherein;

the second set of profile data is indicative of information for the first user over a second period of time;

the second set of profile data is indicative of the user profile for the first user changing over time;

generate an updated user profile for the first user based on the second set of profile data;

match the updated user profile to a second most-similar baseline profile from among the plurality of baseline profiles at the second point in time, wherein second most-similar baseline profile is most-similar to the updated user profile in view of the change to the user profile over time; and

adjust the baseline for measurements of the physiological parameter of the first user based on the second most-similar baseline profile.

11. The processing device of claim 10, wherein:

the instructions are executed on a server;

the first set of profile data or the second set of profile data is received over a communications network; and

the baseline is communicated to a wearable device of the first user over the communications network.

12. The processing device of claim 10, wherein the second set of profile data is for a second user, wherein the second user comprises:

a group of users that is a subset of users corresponding to the plurality of baseline profiles; and

levels of the physiological parameter of the group of users comprise an average of the levels across individuals of the group of users, wherein the baseline is with respect to the group of users.

13. The processing device of claim 10, wherein the instructions further cause the processing device to:

take measurements for the physiological parameter through a sensor;

analyze the measurements with respect to the baseline; and

inform the first user how far above or below the measurements are from the baseline.

14. The processing device of claim 10, further comprising the user interface through which to receive reports or information related to the physiological parameter, wherein the instructions further cause the processing device to:

receive the measurements from a sensor in bodily contact with the first user;

analyze the measurements with respect to the baseline for the first user; and

provide, to the user through the user interface, a report of an analysis of the measurements as related to the baseline for the first user.

15. The processing device of claim 10, wherein the first set of profile data or the second set of profile data further includes family health medical records.

23. The processing device of claim 10, wherein the data of the first set of profile data or the second set of profile data for the first user is weighted based on a statistical variation of the data over time, wherein the statistical variation of the data is indicative of a statistical variation of one or more of the characteristics of the first user changing over time.

24. The processing device of claim 10, wherein processing device is further to dynamically weight the data of the first set of profile data or the second set of profile data based on a signal to noise (SNR) ratio of the data of the first set of profile or the second set of profile data.

16. A wearable device comprising:

a housing formed and shaped to affix to a user and including an indicator;

a power source;

a sensor configured to;

take a first physiological measurement and a second physiological measurement from a body of the user at a first point of time; and

take a third physiological measurement and a fourth physiological measurement from the body of the user at a second point of time; and

a memory device to store information; and

a processing device coupled to the power source and the memory device, the processing device being located within the housing, wherein the processing device is configured to;

receive the first physiological measurement and the second physiological measurement from the sensor;

analyze the first physiological measurement and the second physiological measurement to determine a first correlation between the first physiological measurement and the second physiological measurement, wherein the first correlation is indicative of the user being involved in a physical activity at a third point in time;

analyze the third physiological measurement and the fourth physiological measurement prior to the user engaging in the physical activity at a fourth point in time to predict when the user will be involved in the physical activity based on a second correlation between the third physiological measurement and the fourth physiological measurement being the same as the second correlation between the first physiological measurement and the second physiological measurement; and

alert the user through the indicator to take an action in anticipation of the user engaging in the physical activity at the fourth point in time based on the prediction that the user will be involved in the physical activity at the fourth point in time.

17. The wearable device of claim 16, wherein predicting when the user will be involved in the physical activity further comprises the processing device executing a machine learning program to analyze habits involving activity levels of the user over time based on the analyzed activity data.

18. The wearable device of claim 16, wherein the processing device is further to convey information using the indicator depending on a type of the physical activity or a nature of a specific action to be taken, wherein the specific action comprises at least one of:

to hydrate, to eat, to rest, or to warm up.

19. The wearable device of claim 16, wherein the information comprises activity levels related to geographic locations of the user, and the processing device is further to:

determine a third correlation between the information and the physical activity; and

identify the physical activity as a probable activity the user will undertake based on the third correlation.

20. The wearable device of claim 16, wherein the information stored at the memory device is activity data that includes scheduling data for an upcoming appointment of the user.

21. The wearable device of claim 20, wherein the processing device is further to:

identify additional information that indicates an appointment corresponding to the physical activity relates to a non-physical activity; and

adjust the alert to the user to account for a likelihood that the appointment relates to the non-physical activity.

25. A wearable device comprising:

a housing formed and shaped to affix to a user and including an indicator;

a power source;

a first memory device to store information; and

a processing device coupled to the power source and the first memory device, the processing device being located within the housing, wherein the processing device is configured to;

receive, from an input device, profile information for the user at a first point in time;

store the profile information at the first memory device;

generate a user profile based on the profile information;

query a plurality of baseline profiles stored at the first memory device or a second memory device to determine whether the plurality of baseline profiles includes a first baseline profile that matches the profile information of the user within a threshold matching level;

in response to the plurality of baseline profiles not including the first baseline profile that matches the profile information of the user within the threshold matching level, iteratively update the profile information of the user and query the plurality of baseline profiles until a first matching baseline profile of the plurality of baseline profiles matches the profile information of the user within the threshold matching level; and

set a baseline profile for the user for a physiological parameter of the user, wherein the baseline profile for the physiological parameter of the user is the same as the first matching baseline profile for the physiological parameter;

receive updated profile information for the user at a second point in time, wherein;

the updated profile information is indicative of information for the user over a second period of time;

the updated profile information is indicative of the user profile for the first user changing over time;

query the plurality of baseline profiles stored at the first memory device or the second memory device to determine whether the plurality of baseline profiles includes a second baseline profile that matches the updated profile information of the user within the threshold matching level;

in response to the plurality of baseline profiles not include the second baseline profile that matches the updated profile information of the user within the threshold matching level, iteratively update the updated profile information of the user and query the plurality of baseline profiles until a second matching baseline profile of the plurality of baseline profiles matches the updated profile information of the user within the threshold matching level; and

set the baseline profile for the user for the physiological parameter of the user, wherein the baseline profile for the physiological parameter of the user is the same as the second matching baseline profile for the physiological parameter.