Machine segmentation of sensor measurements and derived values ​​in virtual motion testing

Abstract

This invention provides a system, method, and device for segmenting signal data related to virtual clinical tests. [Solution] A user device can mechanically segment sensor measurements by determining a context window. The context window may include a start point and an end point. The context window can be used to define the period over which the sensor measurements are segmented.

Claims

1. A computer implementation method, The wearable user device accesses (i) a first timing indicator associated with a first time, (ii) a second timing indicator associated with a second time, and (iii) test information identifying the virtual motor test type of the virtual motor test, Accessing signal data acquired by the wearable user device during the period enclosed by the first time and the second time, The wearable user device and, based on the virtual motion test type, determines a first signal data type for segmenting the signal data, wherein the first signal data of the first signal data type is output by a first sensor of the wearable user device during the period. The wearable user device controls the context window within the specified period, at least: Selecting a historical signal profile of the first signal data type, wherein the historical signal profile is derived from previous occurrences of the virtual motion test, and This is determined by comparing the first signal data with the historical signal profile to identify a third time corresponding to the start point of the context window and a fourth time corresponding to the end point of the context window. The wearable user device segments a portion of the signal data received during the context window, A computer implementation method comprising generating a virtual motion test data package based on the portion of the signal data and the test information using the wearable user device.

2. The computer implementation method according to claim 1, further comprising adjusting the operation of the first sensor based on the context window by the wearable user device during a virtual motion test of the virtual motion test type that is performed later.

3. The computer implementation method according to claim 2, wherein the operation includes a sampling rate, and adjusting the sampling rate based on the context window includes instructing the first sensor to capture data at a first sampling rate outside the context window, and instructing the first sensor to capture data at a second sampling rate within the context window.

4. Comparing the first signal data with the historical signal profile is Accessing the set of evaluation rules associated with the aforementioned virtual motor test type, The computer implementation method according to claim 1, further comprising evaluating the first signal data in accordance with the set of evaluation rules to identify the third time point and the fourth time.

5. The computer implementation method according to claim 4, wherein the set of evaluation rules defines signal characteristics indicating the start point and the end point of the context window for the virtual motion test type.

6. The start and end points of the context window are the first start and first end points of the context window, and the method further includes determining a second signal data type for segmenting the signal data by the wearable user device and based on the virtual motion test type, wherein the second signal data of the second signal data type is output by a second sensor of the wearable user device during the period, and the context window is determined within the period. Accessing different sets of evaluation rules associated with the aforementioned virtual motor test type, The computer implementation method according to claim 4, further comprising evaluating the second signal data according to a different set of the evaluation rules to identify a second start point and a second end point of the context window.

7. The computer implementation method according to claim 6, wherein the set of evaluation rules is associated with the first signal data type, and a different set of evaluation rules is associated with the second signal data type.

8. The first starting point is different from the second starting point, and the method determines the actual starting point of the context window. Selecting the actual starting point based on the earlier occurrence of the first or second starting point, and The computer implementation method according to claim 6, further comprising determining the actual starting point by performing one or more of the following: a first signal difference measured between the first starting point and the first signal data at a corresponding first time in the historical signal profile, and a second signal difference measured between the second starting point and the second signal data at a corresponding second time in the historical signal profile.

9. The computer implementation method according to claim 1, wherein the context window includes a start point and an end point, the start point of the context window is associated with a third time that is later than the first time and earlier than the second time, and the end point of the context window is associated with a fourth time that is later than the third time and earlier than the second time.

10. Determining a third timing indicator associated with the third time, and a fourth timing indicator associated with the fourth time, The computer implementation method according to claim 9, further comprising associating the third and fourth timing indicators with the portions of the signal data.

11. The computer implementation method according to claim 1, further comprising generating the test information as part of performing the virtual motion test during the aforementioned period.

12. The wearable user device receives a first user input indicating the starting point of the virtual motion test, In response to receiving the first user input, and based on the first user input, the first timing indicator is generated. The wearable user device receives a second user input indicating the endpoint of the virtual motion test, The computer implementation method according to claim 1, further comprising generating the second timing indicator in response to and based on the second user input.

13. The computer implementation method according to claim 1, wherein each of the first and second timing indicators includes a data tag containing a corresponding timestamp.

14. The computer implementation method according to claim 1, wherein the signal data includes signal data collected from a plurality of sensors of the wearable user device.

15. The computer implementation method according to claim 1, further comprising determining a second signal data type for segmenting the signal data by the wearable user device and based on the virtual motion test type, wherein the second signal data of the second signal data type is output by a second sensor of the wearable user device during the period.

16. The computer implementation method according to claim 15, wherein determining the context window is further based at least in part on the second signal data.

17. The computer implementation method according to claim 1, wherein the portion of the signal data includes at least a portion of the first signal data.

18. The computer implementation method according to claim 1, wherein the portion of the signal data excludes the first signal data.

19. The computer implementation method according to claim 1, wherein the first sensor includes at least one of a gyroscope, an accelerometer, a photoplethysmography sensor, or a heart rate sensor.

20. The computer implementation method according to claim 1, wherein the virtual motion test includes a series of tasks for evaluating the motor function of the wearer of the wearable user device.

21. To generate the results of the virtual motion test, which include the portion of the signal data; The computer implementation method according to claim 1, further comprising outputting a portion of the result, wherein outputting the portion of the result includes at least one of presenting the portion of the result on the display of the wearable user device or transmitting the portion of the result to a remote computing device.

22. The computer implementation method according to claim 1, wherein the virtual motion test is performed during the period, and associating the portion of the signal data with the virtual motion test includes tagging the portion of the signal data with the start and end points of the context window during the period in which the virtual motion test is performed.

23. A computer-readable medium that includes processor-executable instructions causing a computing device to carry out the method according to any one of claims 1 to 23 when executed by one or more processors.

24. A wearable user device comprising a memory for storing computer executable instructions that cause the wearable user device to carry out the method according to any one of claims 1 to 23 when executed by one or more processors.

25. A computer implementation method, The input device of a wearable user device receives a first user input that identifies the starting point of a first period in which a virtual motion test is performed, The input device of the wearable user device receives a second user input that identifies the end point of the first period, Accessing first signal data output by the first sensor of the wearable user device during the first period, based on the virtual motion test, The wearable user device determines a context window within the first period based on the first signal data and the virtual motor test type associated with the virtual motor test, wherein the context window defines a second period within the first period. The wearable user device determines the second signal data output by the second sensor of the wearable user device during the second period, A computer implementation method comprising associating the second signal data with the virtual motion test using the wearable user device.

26. The computer implementation method according to claim 25, wherein the first sensor and the second sensor share common features.

27. The computer implementation method according to claim 26, wherein the common features include an activity metric.

28. The computer implementation method according to claim 25, wherein the first signal data is different from the second signal data.

29. During the second period, a portion of the first signal data output by the first sensor of the wearable user device is segmented, The computer implementation method according to claim 25, further comprising associating the portion of the first signal data with the virtual motion test.

30. Determining the context window within the first period is Accessing the set of evaluation rules associated with the aforementioned virtual motor test type, The method according to claim 25, comprising evaluating the first signal data in accordance with the set of evaluation rules to identify the start point and the end point of the second period.

31. The computer implementation method according to claim 30, wherein the set of evaluation rules defines signal characteristics indicating the start point and the end point of the second period for the virtual motion test type.

32. Determining the context window that defines the second period is Accessing different sets of evaluation rules associated with the aforementioned virtual motor test type, The computer implementation method according to claim 30, further comprising evaluating a portion of a second signal data acquired during the first period according to a different set of the evaluation rules to identify the start point and the end point of the second period.

33. The computer implementation method according to claim 32, wherein the set of evaluation rules is associated with a first signal data type of the first signal data, and a different set of evaluation rules is associated with a second signal data type of the second signal data.

34. The computer implementation method according to claim 25, wherein the input device includes a button or a touchscreen.

35. The computer implementation method according to claim 25, wherein the context window corresponds to the time when the user performs the virtual motion test.

36. A computer-readable medium that includes processor-executable instructions, when executed by one or more processors, causing a computing device to carry out the method according to any one of claims 26 to 36.

37. A wearable user device, which includes a memory for storing computer executable instructions that cause the wearable user device to perform the method according to any one of claims 26 to 36 when executed by one or more processors.

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