Motion determination

• US 8,843,345 B2
• Filed: 06/20/2011
• Issued: 09/23/2014
• 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
• Primary Examiner(s): Nghiem, Michael
• Assistant Examiner(s): Satanovsky, Alexander
• Application Number:
  US13/164,136
• Publication Number:
  US 20120323520A1
• Time in Patent Office: 1,191 Days
• Field of Search: 702/141, 702/189, 702/150, 73/17.9, 735/033
• 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 computer implemented method, comprising:

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

wherein a computer executes instructions for;

determining an average of the data values;

wherein the average of the data values comprises a first order moment;

determining an average of squares of the data values;

wherein the average of the squares of the data values comprises a second order moment;

determining an average of cubes of the data values;

determining a difference between a third order moment calculated only using the average of cubes and a third order moment calculated using only the first and second order moments; and

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

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

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

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

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

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

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

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

10. The computer implemented 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 computer implemented 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 computer implemented method, comprising:

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

wherein a computer executes instructions for;

determining an average of the data values;

wherein the average of the data values comprises a first order moment;

determining an average of squares of the data values;

wherein the average of the squares of the data values comprises a second order moment

determining an average of cubes of the data values;

determining a difference between a third order moment calculated only using the average of cubes and a third order moment calculated using only the first and second order moments; and

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

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

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

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

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

17. The computer implemented 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 motion 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 chip and further configured to run a temperature compensation algorithm, wherein the data signal comprises data values as a function of user motion and noise;

wherein the motion detection algorithm determines an average of the data values;

wherein the average of the data values comprises a first order moment;

determines an average of squares of the data values;

wherein the average of the squares of the data values comprises a second order moment;

determines an average of cubes of the data values;

determines a difference between a third order moment calculated only using the average of cubes and a third order moment calculated using only the first and second order moments; and

determines whether a user motion event has occurred based on the difference;

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.

23. A computer implemented method, comprising:

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

wherein a computer executes instructions for;

determining an average of the data values;

wherein the average of the data values comprises a first order moment;

determining an average of squares of the data values;

wherein the average of the squares of the data values comprises a second order moment;

determining an average of cubes of the data values;

determining a difference based on the equation

V₃=T₃−

(3*T₂*T₁−

2*T₁³),

where V₃ is the difference between the estimated third order moment (T₃) and the theoretical third order moment based on T₁ and T₂, T₁ is the estimated first order moment and T₂ is the estimated second order moment; and

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

24. The computer implemented method of claim 23 further includes:

determining an average of fourth power of the data values;

determining a difference based on the equation

V₄=T₄−

(3*T₂²−

2* T₁⁴+4*V₃*T₁),

where V₄ is the difference between the estimated fourth order moment (T₄) and the theoretical fourth order moment based on estimated T₁, T₂ and V₃, and

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