Systems and Methods for Activity Recognition Training

• US 20140244209A1
• Filed: 01/31/2014
• Published: 08/28/2014
• Est. Priority Date: 02/22/2013
• Status: Abandoned Application

• Current Assignee: Invensense Incorporated (TDK Corporation)
• Original Assignee: Invensense Incorporated (TDK Corporation)
• Inventors: Katingari, Karthik, Lee, Jonathan E.
• Application Number:
  US14/169,782
• Publication Number:
  US 20140244209A1
• Time in Patent Office: Days
• US Class Current: 702/150
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training

Abstract

Systems and methods are disclosed for classifying an activity. A sensor tracks motion by a user and a classifier recognizes data output sensor as corresponding to an activity. The classifier may be trained or otherwise modified using received information, which may include data from the sensor or information from an external source, such as a remotely maintained database. The device may update a local or remote database using sensor data when in a training mode. The training mode may be implemented automatically when there is sufficient confidence in the activity identification or manually in response to a user input.

Claims

1. An activity recognition system comprising:

at least one sensor configured to track motion by a user; and

a classifier configured to recognize a first pattern of data output by the at least one sensor as corresponding to a first activity;

wherein the classifier is configured to he modified by received information.

2. The activity recognition system of claim 1, wherein the classifier comprises a database configured to correlate sensor data with the first activity.

3. The activity recognition system of claim 1, wherein the classifier comprises an algorithm configured to identify the first activity based, at least in part, on the first pattern of data.

4. The activity recognition system of claim 1, wherein the received information comprises data output by the at least one sensor.

5. The activity recognition system of claim 1, wherein the received information comprises information from an external source.

6. The system of claim 1, wherein the first activity comprises an existing activity.

7. The system of claim 1, wherein the first activity comprises a new activity.

8. The system of claim 1, wherein the classifier is configured to he modified by data output by the at least one sensor based, at least in part, on a comparison of sensor data to a confidence threshold.

9. The system of claim 1, wherein the classifier is configured to be modified by data output by the at least one sensor based, at least in part, on a user input.

10. The system of claim 2, wherein the database is maintained remotely.

11. The system of claim 10, wherein the database comprises an aggregation of data from multiple users.

12. The system of claim 2, wherein the database is maintained locally.

13. The system of claim 1, wherein the at least one sensor is coupled to the classifier by a wireless interface.

14. The system of claim 1, wherein the at least one sensor is coupled to the classifier by a wired interface.

15. The system of claim 1, wherein the sensor and the classifier are integrated into the same device.

16. The system of claim 1, wherein the sensor and the classifier are integrated into the same package.

17. The system of claim 1, wherein the sensor and the classifier are integrated into the same chip.

18. The system of claim 1, wherein the sensor comprises at least one sensor selected from the group consisting of an accelerometer, a gyroscope, a pressure sensor, a microphone, and a magnetometer.

19. The system of claim 1, wherein the pattern of data corresponds to an activity selected from the group consisting of walking, running, biking, swimming, rowing, skiing, stationary exercising and driving.

20. A method for recognizing a first activity comprising:

obtaining data from at least one sensor associated with a user;

performing a classification routine to identify a first pattern of data obtained from the at least one sensor as corresponding to the first activity; and

modifying the classification routine based, at least in part, on received information.

21. The activity recognition method of claim 20, wherein the classification routine employs a database configured to correlate sensor data with the first activity.

22. The activity recognition method of claim 20, wherein the classification routine employs an algorithm configured to identify the first activity based, at least in part, on the first pattern of data.

23. The activity recognition method of claim 20, wherein the classification routine is modified using data output by the at least one sensor.

24. The activity recognition method of claim 20 wherein the classification routine is modified using information from an external source.

25. The method of claim 20, wherein the first activity comprises an existing activity.

26. The method of claim 20, wherein the first activity comprises a new activity.

27. The method of claim 20, further comprising comparing the sensor data to a confidence threshold, wherein the classification routine is modified based, at least in part, on the comparison.

28. The method of claim 20, wherein the classification routine is modified by data output by the at least one sensor based, at least in part, on a user input.

29. The method of claim 21, wherein the database is maintained remotely, further comprising uploading sensor data to a server.

30. The method of claim 29, further comprising aggregating data from multiple users in the database.

31. The method of claim 21, further comprising maintaining the database locally.

32. The method of claim 20, further comprising coupling the at least one sensor to a device configured to perform the classification routine with a wireless interface.

33. The method of claim 20, further comprising coupling the at least one sensor to a device configured to perform the classification routine with a wired interface.

34. The method of claim 20, wherein the sensor comprises at least one sensor selected from the group consisting of an accelerometer, a gyroscope, a pressure sensor, a microphone, and a magnetometer.

35. The method of claim 20, wherein the pattern of data corresponds to an activity selected from the group consisting of walking, running, biking, swimming, rowing, skiing, stationary exercising and driving.