Waistband monitoring analysis for a user

• US 10,251,598 B2
• Filed: 05/11/2016
• Issued: 04/09/2019
• Est. Priority Date: 05/11/2016
• Status: Active Grant

• Current Assignee: CarePredict, Inc.
• Original Assignee: CarePredict, Inc.
• Inventors: Barnes, Ronald A., Elam, Jr., David P., Ibey, Bennett L., Shahhaidar, Ehsaneh, Wilmink, Gerald J., Wilson, Jason B., Womble, Daniel O.
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Morales, Jon Eric C
• Application Number:
  US15/152,443
• Publication Number:
  US 20170325740A1
• Time in Patent Office: 1,063 Days
• Field of Search: 607 6
• 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 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1117 Fall detection
• 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 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/4875 Hydration status, fluid retention of the body
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses

Abstract

Methods, apparatuses, and computer readable mediums for waistband monitoring analysis for a user are provided. In a particular embodiment, a waistband monitoring device is configured to generate a motion pattern based on motion data from a motion sensor coupled to the waistband monitoring device; receive physiological data generated by a physiological sensor coupled to the waistband monitoring device, wherein the physiological data indicates at least one vital sign of the user; identify an activity of the user that corresponds to the motion data and the physiological data; and generate an analysis of the user'"'"'s performance of the identified activity based on the motion data and the physiological data.

Claims

1. A method of waistband monitoring analysis, the method comprising:

providing a waistband monitoring device coupled to a waistband worn around the waist of a user, the waistband monitoring device comprising one or more motion sensors and one or more physiological sensors in communication with an analysis controller, the waistband monitoring device integrated with the waistband;

receiving, via the one or more motion sensors, motion data of the user;

generating, by the analysis controller, a motion pattern based on the motion data received from the one or more motion sensors;

receiving, by the analysis controller, physiological data generated by the one or more physiological sensors, wherein the physiological data indicates at least one vital sign of the user;

identifying, by the analysis controller, one or more activities of the user that corresponds to the motion data and the physiological data, wherein an activity of the one or more of the activities is sleeping;

comparing, by the analysis controller, the motion pattern to a predetermined activity pattern corresponding to the identified activity of the one or more activities of the user;

evaluating, by the analysis controller, a user'"'"'s performance of the identified activity by determining whether there are one or more differences between the motion pattern and the predetermined activity pattern;

identifying, by the analysis controller, that there are one or more differences between the motion pattern and the predetermined activity pattern; and

based on the determination, transmitting a visual output that displays an analysis of the user'"'"'s performance of the identified activity based on the comparison between the motion pattern and the predetermined activity pattern, wherein the analysis comprises analyzing one or more of;

a total time that the user was asleep, times that the user spent in sleep stages, a time for the user to fall asleep, and an indication of the amount that the user moved while asleep.

2. The method of claim 1 wherein comparing, by the analysis controller, the motion pattern to a predetermined activity pattern corresponding to the identified activity of the user, comprises:

comparing the motion data used to generated the motion pattern with a stored motion pattern selected from a plurality of stored motion patterns, wherein each stored motion pattern is predefined to correspond with a particular activity.

3. The method of claim 1 wherein the one or more activities comprises a further activity that is a particular exercise activity and the analysis further comprises analyzing one or more of:

a total time that the user spent performing the exercise activity and a caloric output that the user expended performing the exercise activity.

4. The method of claim 1 wherein identifying one or more activities of the user that corresponds to the motion data and the physiological data comprises:

substantially matching to an activity pattern one of;

the motion data and the physiological data.

5. The method of claim 1 wherein identifying one or more activities of the user that corresponds to the motion data and the physiological data comprises:

identifying the activity based on environmental condition data and a historical activity pattern.

6. The method of claim 1 wherein the physiological data includes at least one of a hydration level measurement, a heart rate measurement, an ECG measurement, a respiration measurement, a pulse oximeter measurement, and a temperature of the user.

7. The method of claim 1 wherein the waistband monitoring device is within a pocket of the waistband.

8. The method of claim 1 wherein the waistband monitoring device is coupled to the waistband via an attachment.

9. A waistband monitoring device for coupling to a waistband of a user to perform waistband monitoring analysis of the user, the waistband monitoring device comprising one or more motion sensors and one or more physiological sensors in communication with an analysis controller, the analysis controller comprising a computer processor and computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the apparatus to perform an operation, comprising:

receiving, via the one or more motion sensors, motion data of the user;

generating a motion pattern based on the motion data received from the one or more motion sensors;

receiving physiological data generated by the one or more physiological sensors, wherein the physiological data indicates at least one vital sign of the user;

identifying one or more activities of the user that corresponds to the motion data and the physiological data, wherein an activity of the one or more activities is sleeping;

comparing the motion pattern to a predetermined activity pattern corresponding to the identified activity of the one or more activities of the user;

evaluating a user'"'"'s performance of the identified activity by determining whether there are one or more differences between the motion pattern and the predetermined activity pattern;

identifying that there are one or more differences between the motion pattern and the predetermined activity pattern; and

based on the determination, transmitting a visual output that displays an analysis of the user'"'"'s performance of the identified activity based on the comparison between the motion pattern and the predetermined activity pattern, wherein the analysis comprises analyzing one or more of;

a total time that the user was asleep, times that the user spent in sleep stages, a time for the user to fall asleep, and an indication of the amount that the user moved while asleep.

10. The apparatus of claim 9 wherein comparing the motion pattern to the predetermined activity pattern corresponding to the identified activity of the user, comprises:

comparing the motion data with a stored motion pattern selected from a plurality of stored motion patterns, wherein each stored motion pattern is predefined to correspond with a particular activity.

11. The apparatus of claim 9 wherein the one or more activities comprises a further activity that is a particular exercise activity and the analysis further comprises analyzing one or more of:

a total time that the user spent performing the exercise activity and a caloric output that the user expended performing the exercise activity.

12. The apparatus of claim 9 wherein identifying one or more activities of the user that corresponds to the motion data and the physiological data comprises:

substantially matching to an activity pattern one of;

the motion data and the physiological data.

13. The apparatus of claim 9 wherein identifying one or more activities of the user that corresponds to the motion data and the physiological data comprises:

identifying the activity based on environmental condition data and a historical activity pattern.

14. The apparatus of claim 9 wherein the physiological data includes at least one of a hydration level measurement, a heart rate measurement, an ECG measurement, a pulse oximeter measurement, a respiration measurement, and a temperature of the user.

15. A non-transitory computer readable storage medium in communication with one or more motion sensors and one or more physiological sensors, the non-transitory computer readable medium including one or more sequences of instructions, which, when executed by one or more processors, cause the one or more processors to perform operations, comprising:

receiving, via the one or more motion sensors, motion data of the user;

generating a motion pattern based on the motion data received from the one or more motion sensors;

receiving physiological data generated by the one or more physiological sensors, wherein the physiological data indicates at least one vital sign of the user;

identifying one or more activities of the user that corresponds to the motion data and the physiological data, wherein an activity of the one or more activities is sleeping;

comparing the motion pattern to a predetermined activity pattern corresponding to the identified activity of the one or more activities of the user;

evaluating a user'"'"'s performance of the identified activity by determining whether there are one or more differences between the motion pattern and the predetermined activity pattern;

identifying that there are one or more differences between the motion pattern and the predetermined activity pattern; and

based on the determination, transmitting a visual output that displays an analysis of the user'"'"'s performance of the identified activity based on the comparison between the motion pattern and the predetermined activity pattern, wherein the analysis comprises analyzing one or more of;

a total time that the user was asleep, times that the user spent in sleep stages, a time for the user to fall asleep, and an indication of the amount that the user moved while asleep.

16. The non-transitory computer readable storage medium of claim 15 wherein comparing the motion pattern to a predetermined activity pattern corresponding to the identified activity of the user, comprises:

comparing the motion data used to generated the motion pattern with a stored motion pattern selected from a plurality of stored motion patterns, wherein each stored motion pattern is predefined to correspond with a particular activity.

17. The non-transitory computer readable storage medium of claim 15 wherein the one or more activities comprises a further activity that is a particular exercise activity and the one or more indications of the analysis further comprises analyzing one or more of:

a total time that the user spent performing the exercise activity and a caloric output that the user expended performing the exercise activity.