Frequency domain adaptive motion cancellation filter

• US 10,772,567 B2
• Filed: 12/23/2015
• Issued: 09/15/2020
• Est. Priority Date: 12/23/2015
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Pickett, Matthew D.
• Primary Examiner(s): Tejani, Ankit D
• Application Number:
  US16/064,047
• Publication Number:
  US 20180368777A1
• Time in Patent Office: 1,728 Days
• Field of Search: None
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• 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 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 Arm or wrist
• 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: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: G06F 17/16 Matrix or vector computation , e.g. matrix-matrix or matrix-vector multiplication, matrix factorization matrix transposition G06F7/78

Abstract

Various systems and methods for implementing frequency domain adaptive motion cancellation filters. An example method includes receiving an optical signal representative of a physiological function. The example method further includes receiving a motion signal from an accelerometer. From the motion signal, a known motion spectrum is expressed as a sum of a product of coefficients for each component of the motion spectrum, wherein the coefficients are representative of the strength of the coupling between the motion signal and the optical signal. The example method may further include determining the coefficients of the motion spectrum using gradient descent and generating a decontaminated optical signal based on the optical signal and the motion model spectrum. Other systems, apparatuses, and methods are described.

Claims

1. An apparatus comprising:

an accelerometer configured to provide a motion signal representative of motion by a user wearing the apparatus;

an optical sensor; and

one or more processors to

receive an optical signal representative of a physiological function from the optical sensor;

receive a motion signal from the accelerometer;

evaluate a motion spectrum, based on the motion signal, expressed as a sum of a product of coefficients for axial components of the motion spectrum to generate an expression of a motion model;

solve an objective function to determine values for the coefficients, wherein the coefficients are representative of the strength of motion signal coupling to the optical signal, to generate the motion model; and

generate a decontaminated signal based on the motion model and the optical signal.

2. The apparatus of claim 1, wherein the one or more processors are further configured to:

provide the decontaminated signal for processing to detect a parameter of the physiological function.

3. The apparatus of claim 1, wherein solving the objective function includes implementing gradient descent.

4. The apparatus of claim 3, wherein solving the objective function includes solving an equation according to c_n=c_n-1−

Γ

g(c_n-1),

where Γ

is a rate parameter to be tuned by validation data, c_n is a vector of coefficients for axial components of the motion spectrum, and g represents the gradient of the motion spectrum at a point.

5. The apparatus of claim 1, wherein each operation is performed in the frequency domain.

6. The apparatus of claim 1, wherein the axial components include at least two of an x-axis component of motion, a y-axis component of motion, and a z-axis component of motion.

7. The apparatus of claim 1, wherein the decontaminated signal is calculated as a difference between a measured optical spectrum f_o and a motion spectrum f_m, and wherein the method further includes a normalization operation.

8. A method comprising:

receiving an optical signal representative of a physiological function;

receiving a motion signal from an accelerometer;

evaluating a motion spectrum, based on the motion signal, expressed as a sum of a product of coefficients for axial components of the motion spectrum to generate an expression of a motion model;

solving an objective function to determine values for the coefficients, wherein the coefficients are representative of the strength of motion signal coupling to the optical signal, to generate the motion model; and

generating a decontaminated signal based on the motion model and the optical signal.

9. The method of claim 8, further comprising:

providing the decontaminated signal for processing to detect a parameter of the physiological function.

10. The method of claim 8, wherein solving the objective function includes implementing gradient descent.

11. The method of claim 10, wherein solving the objective function includes solving an equation according to c_n=c_n-1−

Γ

g(c_n-1),

where Γ

is a rate parameter to be tuned by validation data, c_n is a vector of coefficients for axial components of the motion spectrum, and g represents the gradient of the motion spectrum at a point.

12. The method of claim 8, wherein each operation is performed in the frequency domain.

13. The method of claim 8, wherein the axial components include at least two of an x-axis component of motion, a y-axis component of motion, and a z-axis component of motion.

14. The method of claim 8, wherein the decontaminated signal is calculated as a difference between a measured optical spectrum f_o and a motion spectrum f_m, and wherein the method further includes a normalization operation.

15. A non-transitory computer-readable storage medium that stores instructions for execution by one or more processors to perform operations for optical monitoring of physiological functions, the operations to configure the one or more processors to:

receive an optical signal representative of a physiological function;

receive a motion signal from an accelerometer;

evaluate a motion spectrum, based on the motion signal, expressed as a sum of a product of coefficients for axial components of the motion spectrum to generate an expression of a motion model;

solve an objective function to determine values for the coefficients, wherein the coefficients are representative of the strength of motion signal coupling to the optical signal, to generate the motion model; and

generate a decontaminated signal based on the motion model and the optical signal.

16. The non-transitory computer-readable storage medium of claim 15, wherein the operations further configure the one or more processors to:

provide the decontaminated signal for processing to detect a parameter of the physiological function.

17. The non-transitory computer-readable storage medium of claim 15, wherein solving the objective function includes implementing gradient descent.

18. The non-transitory computer-readable storage medium of claim 17, wherein the operations further configure the one or more processors to:

solve an equation according to c_n=c_n-1−

Γ

g(c_n-1), where Γ

is a rate parameter to be tuned by validation data, c_n is a vector of coefficients for axial components of the motion spectrum, and g represents the gradient of the motion spectrum at a point.

19. The non-transitory computer-readable storage medium of claim 15, wherein each operation is performed in the frequency domain.

20. The non-transitory computer-readable storage medium of claim 15, wherein the axial components include at least two of an x-axis component of motion, a y-axis component of motion, and a z-axis component of motion.

21. The non-transitory computer-readable storage medium of claim 15, wherein the decontaminated signal is calculated as a difference between a measured optical spectrum f_o and a motion spectrum f_m, and wherein the method further includes a normalization operation.