Determining baseline contexts and stress coping capacity

• US 10,478,131 B2
• Filed: 06/15/2016
• Issued: 11/19/2019
• Est. Priority Date: 07/16/2015
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Jain, Jawahar, Young, James, Wortham, Cody, Sadi, Sajid, Mistry, Pranav
• Primary Examiner(s): Schaetzle, Kennedy
• Application Number:
  US15/183,472
• Publication Number:
  US 20170071537A1
• Time in Patent Office: 1,252 Days
• Field of Search: None
• CPC Class Codes: A61B 2503/10 Athletes
• CPC Class Codes: A61B 2560/0209 adapted for power saving
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0013 Medical image data A61B1/00011, A61B6/56, A61B8/56 take precedence
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/4884 inducing physiological or psychological stress, e.g. applications for stress testing
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6833 Adhesive patches
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• 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 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 : Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/7405 : using sound
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7455 : characterised by tactile indication, e.g. vibration or electrical stimulation
• 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: A61B 5/7475 : User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G16H 40/60 : for the operation of medical equipment or devices
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 40/67 : for remote operation

Abstract

A method for monitoring a health characteristic of a user based on one or more biological measurements may include selecting a context from a plurality of contexts, each context corresponding to a baseline health value, and each context being defined by a plurality of recorded events each comprising one or more of repeated biological states, repeated user activity, or space-time coordinates of the user, and then monitoring the health characteristic of the user based on one or more bio-sensing measurements in comparison to the baseline health value corresponding to the selected context.

Claims

1. A method for monitoring a health characteristic of a user based on one or more biological measurements, comprising:

determining a current context of a user;

accessing a plurality of contexts for the user, wherein;

each of the plurality of contexts identifies a context-specific baseline health value; and

each of the plurality of contexts is defined at least in part by a plurality of recorded events each comprising one or more of repeated biological states, repeated user activity, or space-time coordinates of the user;

identifying from the plurality of contexts a predefined user context corresponding to the current context of the user;

monitoring the health characteristic of the user based on one or more bio-sensing measurements in comparison to the context-specific baseline health value corresponding to the identified predefined user context;

detecting, based on monitoring the health characteristic, a plurality of event pairs, each event pair comprising;

a first event corresponding to the health characteristic of the user being within a first pre-defined variability zone; and

a second event corresponding to the health characteristic of the user being within a second pre-defined variability zone;

determining, for each event pair, an amount of time between the first and second event; and

determining a context-specific health-resiliency measurement specific to the user, the identified predefined user context, and the health characteristic by averaging over the plurality of event pairs the determined amount of time between the first and second events.

2. The method of claim 1, wherein the one or more bio-sensing measurements comprises one or more health measurements received from one or more sensors of an electronic device of the user.

3. The method of claim 1, wherein determining the current context of the user comprises:

receiving a plurality of current-context measurements from an electronic device of the user; and

determining the current context based on one or more of the received current-context measurements.

4. The method of claim 3, wherein the current context is automatically determined by the electronic device of the user.

5. The method of claim 1, wherein the context-specific baseline health value identified by each of the plurality of contexts is user-specific.

6. The method of claim 1, wherein the health characteristic corresponds to an estimated stress level of the user.

7. The method of claim 6, wherein the context-specific baseline health value corresponds to a baseline stress level of the user for that particular one of the plurality of contexts.

8. The method of claim 1, wherein the health characteristic corresponds to an estimated heart rate of the user.

9. The method of claim 1, wherein the health characteristic corresponds to an estimated heart-rate variability (HRV) of the user.

10. The method of claim 1, further comprising:

generating a first context by identifying a pattern of repeated biological states or repeated activity of the user based on the bio-sensing measurements; and

determining a baseline health value associated with the first context.

11. The method of claim 10, wherein an electronic device of the user automatically generates the first context based on the identified patterns.

12. The method of claim 10, wherein an electronic device of the user automatically detects one or more new contexts that are different than any of the plurality of contexts.

13. The method of claim 1, wherein the health characteristic is stored on an electronic device of the user or on another device associated with the electronic device.

14. The method of claim 1, wherein:

the health characteristic corresponds to an estimated stress level of the user;

the first event is associated with a stress event;

the second event is associated with a relaxation event; and

the health-resiliency measurement is a measurement of the amount of time it takes for the user to recover from the stress event to the relaxation event.

15. One or more computer-readable non-transitory storage media embodying software for monitoring a health characteristic of a user based on one or more biological measurements, that is operable when executed to:

determine a current context of a user;

access a plurality of contexts for the user, wherein;

each of the plurality of contexts identifies a context-specific baseline health value; and

each of the plurality of contexts is defined at least in part by a plurality of recorded events each comprising one or more of repeated biological states, repeated user activity, or space-time coordinates of the user;

identify from the plurality of contexts a predefined user context corresponding to the current context of the user;

monitor the health characteristic of the user based on one or more bio-sensing measurements in comparison to the context-specific baseline health value corresponding to the identified predefined user context;

detect, based on monitoring the health characteristic, a plurality of event pairs, each event pair comprising;

a first event corresponding to the health characteristic of the user being within a first pre-defined variability zone; and

a second event corresponding to the health characteristic of the user being within a second pre-defined variability zone;

determine, for each event pair, an amount of time between the first and second event; and

determine a context-specific health-resiliency measurement specific to the user, the identified predefined user context, and the health characteristic by averaging over the plurality of event pairs the determined amount of time between the first and second events.

16. The media of claim 15, wherein the health characteristic corresponds to an estimated stress level of the user.

17. The media of claim 16, wherein:

the first event is associated with a stress event;

the second event is associated with a relaxation event; and

the health-resiliency measurement is a measurement of the amount of time it takes for the user to recover from the stress event to the relaxation event.

18. A system comprising:

one or more processors; and

a non-transitory memory coupled to the processors comprising instructions executable by the processors for monitoring a health characteristic of a user based on one or more biological measurements, the processors operable when executing the instructions to;

determine a current context of a user;

access a plurality of contexts for the user, wherein;

each of the plurality of contexts identifies a context-specific baseline health value; and

each of the plurality of contexts is defined at least in part by a plurality of recorded events each comprising one or more of repeated biological states, repeated user activity, or space-time coordinates of the user;

identify from the plurality of contexts a predefined user context corresponding to the current context of the user;

monitor the health characteristic of the user based on one or more bio-sensing measurements in comparison to the context-specific baseline health value corresponding to the identified predefined user context;

detect, based on monitoring the health characteristic, a plurality of event pairs, each event pair comprising;

a first event corresponding to the health characteristic of the user being within a first pre-defined variability zone; and

a second event corresponding to the health characteristic of the user being within a second pre-defined variability zone;

determine, for each event pair, an amount of time between the first and second event; and

determine a context-specific health-resiliency measurement specific to the user, the identified predefined user context, and the health characteristic by averaging over the plurality of event pairs the determined amount of time between the first and second events.

19. The system of claim 18, wherein the health characteristic corresponds to an estimated stress level of the user.

20. The system of claim 19, wherein:

the first event is associated with a stress event;

the second event is associated with a relaxation event; and

the health-resiliency measurement is a measurement of the amount of time it takes for the user to recover from the stress event to the relaxation event.