MOTION DETERMINATION

• US 20120323520A1
• Filed: 06/20/2011
• Published: 12/20/2012
• Est. Priority Date: 06/20/2011
• Status: Active Grant

• Current Assignee: Invensense Incorporated (TDK Corporation)
• Original Assignee: Invensense Incorporated (TDK Corporation)
• Inventors: Keal, William Kerry
• Granted Patent: US 8,843,345 B2
• Time in Patent Office: Days
• US Class Current: 702/141
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: G01C 19/5776 Signal processing not specific to any of the devices covered by groups G01C19/5607 - G01C19/5719
• CPC Class Codes: G01C 25/005 initial alignment, calibration or starting-up of inertial devices
• CPC Class Codes: G01P 15/16 by evaluating the time-derivative of a measured speed signal
• CPC Class Codes: G01P 15/18 in two or more dimensions

Abstract

Described herein are systems and methods that can employ a motion detection algorithm to determine whether a sensor has experienced a motion event or a no motion event. The sensor can be any sensor that can be used to identify and/or characterize motion. Upon receiving a signal from the sensor, moments of the signal can be calculated. Then, the moments can be compared to determine whether the signal is Gaussian. If the signal is a Gaussian signal, the algorithm determines that the signal is due to a no motion event. If the signal is a non-Gaussian signal, the algorithm determines that the signal is due to a motion event.

Claims

1. A method, comprising:

receiving a data signal from a sensor, wherein the data signal comprises data values as a function of user motion and noise;

determining an average of the data values;

determining an average of squares of the data values;

determining an average of cubes of the data values;

determining a difference between the average of the cubes and an expected third order moment, wherein the expected third order moment is calculated from the average of the squares and the average of the data values; and

determining whether a user motion event has occurred based on the difference.

2. The method of claim 1, wherein the determining further comprises determining that no user motion has occurred when the difference is within a threshold range.

3. The method of claim 2, wherein the receiving the data signal comprises receiving the data signal from an accelerometer.

4. The method of claim 2, wherein the receiving the data signal comprises receiving the data signal from a compass.

5. The method of claim 2, wherein the receiving the data comprises receiving the data from a gyroscope.

6. The method of claim 5, further comprising setting a gyroscope bias when no user motion has occurred.

7. The method of claim 5, wherein the setting further comprises setting the gyroscope bias to the average of the data values.

8. The method of claim 5, wherein the determining further comprising setting a gyroscope temperature compensation learning term when no user motion has occurred.

9. The method of claim 1, wherein the noise is Gaussian noise.

10. The method of claim 1, further comprising:

determining an average of fourth powers of the data values;

determining a second difference between the average of the fourth powers and an expected fourth order moment, wherein the expected fourth order moment is calculated from the average of the squares and the average of the data values; and

determining whether a user motion event has occurred based on the second difference.

11. The method of claim 1, further comprising:

determining an average of fourth powers of the data values;

determining an average of fifth powers of the data values;

determining a third difference between the average of the fifth powers and an expected fifth order moment, wherein the expected fifth order moment is calculated from the from the average of the squares and the average of the data values; and

determining whether a user motion event has occurred based on the third difference.

12. A method, comprising:

receiving a data signal from a sensor, wherein the data signal comprises data values as a function of motion and noise, when the sensor is known not to be moving;

determining an average of the data values;

determining an average of squares of the data values;

determining an average of cubes of the data values;

determining a difference between the average of the cubes and an expected third order moment, wherein the expected third order moment is calculated from the average of the squares and the average of the data values; and

determining whether the sensor is working properly based on the difference.

13. The method of claim 12, wherein the determining whether the sensor is working properly further comprising confirming that the sensor has recorded a no motion event if the difference is within a threshold range.

14. The method of claim 12, wherein the receiving the data signal further comprises receiving the data signal from an accelerometer.

15. The method of claim 12, wherein the receiving the data signal further comprises receiving the data signal from a compass.

16. The method of claim 12, wherein the receiving the data signal further comprises receiving the data signal from a gyroscope.

17. The method of claim 12, further comprising:

determining an average of fourth powers of the data values;

determining a second difference between the average of the fourth powers and an expected fourth order moment, wherein the expected fourth order moment is calculated from the average of the squares and the average of the data values; and

determining whether the sensor is working properly based on the second difference.

18. A system, comprising:

a sensor chip comprising a gyroscope and a first processor configured to run a motion detection algorithm on data from the gyroscope;

a host device communicatively coupled to the sensor chip comprising a second processor configured to independently run the motion detection algorithm on the data from the sensor and further configured to run a temperature compensation algorithm,

wherein when the motion detection algorithm running on the first processor detects a no motion event, the second processor records a bias for the gyroscope that is used within the temperature compensation algorithm.

19. The system of claim 18, wherein the host device is communicatively coupled to the sensor chip via an I2C bus or a serial port.

20. The system of claim 18, wherein the host device utilizes the data from the gyroscope to feed the motion detection algorithm.

21. The system of claim 18, wherein the first processor is configured to determine that no motion has occurred upon an end of a time period or a temperature change and to utilize the bias for the gyroscope.

22. The system of claim 18, wherein the second processor is configured to run the motion detection algorithm in parallel with the first processor.