Health habit management

Patent metadata

Field	Value
Publication number	US-2019074076-A1
Application number	US-201615549253-A
Country	US
Kind code	A1
Filing date	Feb 17, 2016
Priority date	Feb 24, 2015
Publication date	Mar 7, 2019
Grant date	—

Abstract

Methods and systems for managing a user's health habits. Various embodiments of the invention allow the user to register habits to a habit registry. Relevant sensor and other data is collected contemporaneously with the registration of the behavior and is stored in association with the registered habit. In normal use, a configured processor attempts to detect occurrences of a previously registered habit by comparing subsequently collected data to previously stored data. When collected and stored data match, a registered health habit is detected, the occurrence may be added to a health habit log, and the feedback may be provided to the user. The feedback assists the user to achieve his goals in health habit management.

First claim

1 . A method for managing a user's health habits with a computing unit, the method comprising:
receiving user data at said computing unit from at least one data source; receiving a registration of a health habit at a user interface during or soon after performance of the health habit; associating said user data with the health habit in response to the receipt of the registration of the health habit; and providing context-appropriate feedback corresponding to recurrence of the health habit based on the association.

2 . The method of claim 1 , further comprising identifying a registered health habit from subsequently received user data by matching the subsequently received user data with the user data associated with the registered health habit.

3 . The method of claim 2 , wherein identifying a registered health habit comprises computing a cross-correlation between the subsequently received user data and the user data associated with the registered health habit.

4 . The method of claim 2 , wherein providing feedback to the user is based on the identified health habit.

5 . The method of claim 4 , wherein the feedback concerns at least one of the user data associated with the health habit, the subsequently received user data, and differences between the user data associated with the health habit and the subsequently received user data.

6 . The method of claim 1 , wherein the user data is selected from the group consisting of the user's calendar data, the user's communication data, the user's vital signs data, the user's motion data, the user's position data, the user's electronic transaction data, the user's height above sea level, the identity of specific persons nearby the user, and the user's weather data.

7 . The method of claim 1 , wherein the at least one data source is selected from the group consisting of an accelerometer, an audio sensor, a video sensor, a location sensor, a movement sensor, an orientation sensor, a skin conductance sensor, a respiration sensor, a glucose level sensor, and a heart rate sensor.

8 . (canceled)

9 . The method of claim 1 , wherein the health habit is suggested by the computing unit prior to registration.

10 . A system for managing a user's health habits, the system comprising:
a processor; at least one data source; and computer executable instructions operative on the processor for:
receiving user data from the at least one data source;
receiving a registration of a health habit at a user interface during or soon after performance of the health habit;
associating the user data with the health habit in response to the receipt of the registration of the health habit; and
providing context-appropriate feedback corresponding to recurrence of the health habit based on the association.

11 . The system of claim 10 , further comprising computer executable instructions operative on the processor for identifying a registered health habit from received user data by matching subsequently received user data with the user data associated with the registered health habit.

12 . The system of claim 11 , further comprising computer executable instructions operative on the processor for providing the feedback to the user based on the identified health habit.

13 . The system of claim 10 , wherein the user data is selected from the group consisting of the user's calendar data, the user's communication data, the user's vital signs data, the user's motion data, the user's position data, the user's electronic transaction data, and the user's weather data.

14 . The system of claim 12 , wherein the feedback concerns at least one of the user data associated with the health habit, the subsequently received user data, and differences between the user data associated with the health habit and the subsequently received user data.

15 . The system of claim 11 , wherein the computer executable instructions for identifying a registered health habit comprise computer executable instructions for computing a cross-correlation between the subsequently received user data and the user data associated with the registered health habit.

16 . The system of claim 10 , wherein the at least one data source is selected from the group consisting of an accelerometer, an audio sensor, a video sensor, a location sensor, a movement sensor, an orientation sensor, and a heart rate sensor.

17 . (canceled)

18 . The system of claim 10 , further comprising computer executable instructions operative on the processor for suggesting the health habit that is subsequently registered.

19 . A non-transitory computer readable storage medium comprising executable code that, when executed by a processor causes the processor to:
receive user data from at least one data source; receive a registration of a health habit at a user interface during or soon after performance of the health habit; associate the user data with the health habit in response to the receipt of the registration of the health habit; and provide context-appropriate feedback corresponding to recurrence of the health habit based on the association.

20 . The non-transitory computer readable storage medium of claim 19 , wherein the executable code, when executed by the processor, causes the processor to match subsequently received user data with the user data associated with the registered health habit.

21 . The non-transitory computer readable storage medium of claim 20 , wherein the executable code, when executed by the processor, causes the processor to provide feedback to the user based on the identified health habit.

22 . The non-transitory computer readable storage medium of claim 19 , wherein the user data is selected from the group consisting of the user's calendar data, the user's communication data, the user's vital signs data, the user's motion data, the user's position data, the user's electronic transaction data, and the user's weather data.

23 . The non-transitory computer readable storage medium of claim 21 , wherein the feedback concerns at least one of the user data associated with the health habit, the subsequently received user data, and differences between the user data associated with the health habit and the subsequently received user data.

24 . The non-transitory computer readable storage medium of claim 20 , wherein the executable code, when executed by the processor, causes the processor to compute a cross-correlation between the subsequently received user data and the user data associated with the registered health habit.

25 . (canceled)

26 . The non-transitory computer readable storage medium of claim 19 , wherein the executable code, when executed by the processor, causes the processor to suggest the health habit that is subsequently registered.

Assignees

• Koninklijke Philips Nv

Inventors

• Harma Aki Sakari
• Krans Jan Martijn
• Lowet Dietwig Jos Clement
• Van Dantzig Saskia

Classifications

• G16H80/00

  ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring · CPC title

• G16H50/70

  for mining of medical data, e.g. analysing previous cases of other patients · CPC title

• G16H10/60

  for patient-specific data, e.g. for electronic patient records · CPC title

• G16H20/00 Primary

  ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance · CPC title

• G16H20/70

  relating to mental therapies, e.g. psychological therapy or autogenous training · CPC title