REMOVING MOTION ARTIFACTS FROM A PHYSIOLOGICAL SIGNAL

• US 20170071545A1
• Filed: 09/14/2016
• Published: 03/16/2017
• Est. Priority Date: 09/14/2015
• Status: Abandoned Application

• Current Assignee: Whoop, Inc.
• Original Assignee: Whoop, Inc.
• Inventors: Ritscher, David E., Tavakoli, Behnoosh, Ghannad-Rezaie, Mostafa
• Application Number:
  US15/265,792
• Publication Number:
  US 20170071545A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/347 Detecting the frequency distribution of signals
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• 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

Abstract

A physiological signal such as a heart rate acquired from a monitoring device is processed to reduce interference, ambiguity, or artifacts arising during various activities. For example, the system can process a physiological signal to account for motion artifacts in the physiological signal and, thus, reduce the impact of movement on the physiological signal. Additionally, or alternatively, the system can process a physiological signal based on one or more measurement contexts associated with a wearable device. In general, the physiological signal processed as described herein can be useful as a reliable, continuous indication of a physiological parameter and, thus, can serve as the basis for other physiological assessments (e.g., heart rate variability) derived from the physiological parameter.

Claims

1. A method for mitigating motion artifacts in a physiological signal from a wearable physiological monitoring device, the method comprising:

acquiring a physiological signal with a device over time, wherein the device is a wearable device for physiological monitoring, and further wherein the physiological signal is indicative of a physical state of a wearer of the device;

measuring motion of the device as a motion signal over time;

determining a fundamental frequency of a spectrum of the motion signal; and

applying a group of notch filters to the physiological signal, wherein the group of notch filters attenuate the fundamental frequency of the motion signal and one or more related frequencies of the motion signal to provide a filtered physiological signal.

2. The method of claim 1, wherein the one or more related frequencies include one or more harmonics of the fundamental frequency.

3. The method of claim 1, wherein the one or more related frequencies include a number of frequencies selected based on a model using multiplicative modulation of the physiological signal and the motion signal.

4. The method of claim 1, wherein the physiological signal is a signal indicative of a heart rate of the wearer.

5. The method of claim 1, wherein acquiring the physiological signal includes receiving a photoplesmythography signal from the device.

6. The method of claim 1, wherein measuring the motion of the device includes detecting the motion with one or more accelerometers.

7. The method of claim 1, wherein measuring the motion of the device includes detecting the motion in a predetermined axis of the device.

8. The method of claim 7, wherein the predetermined axis is normal to a measurement surface of the wearer in contact with the device.

9. The method of claim 1, wherein determining the fundamental frequency includes identifying a dominant peak in the spectrum of the motion signal.

10. The method of claim 1, wherein determining the fundamental frequency includes identifying the fundamental frequency using at least one of a harmonic product spectrum and a complex cepstrum of the spectrum of the motion signal.

11. The method of claim 1, further comprising preprocessing the spectrum of the motion signal to remove one or more artifacts arising from time domain discontinuities in the motion signal.

12. The method of claim 1, wherein applying the group of notch filters includes post-processing the physiological signal on a remote computing resource that receives the physiological signal and the motion signal from the device.

13. The method of claim 1, further comprising creating a model of a relationship between the motion and the physiological signal and applying the model to attenuate an artifact of the motion signal in the physiological signal.

14. A computer program product comprising non-transitory computer executable code embodied in a non-transitory computer-readable medium that, when executing on one or more computing devices, performs the steps of:

acquiring a physiological signal over time from a device for physiological monitoring, the physiological signal indicative of a physical state of a wearer of the device;

measuring motion of the device as a motion signal over time;

determining a fundamental frequency of a spectrum of the motion signal; and

applying a notch filter to the physiological signal, wherein the notch filter attenuates the fundamental frequency of the motion signal and one or more related frequencies of the motion signal to provide a filtered physiological signal.

15. The computer program product of claim 14, wherein the one or more related frequencies include one or more harmonics of the fundamental frequency.

16. The computer program product of claim 14, wherein the one or more related frequencies include a number of frequencies selected based on a physical model of the device and the wearer, the physical model including multiplicative modulation of the physiological signal and the motion signal.

17. The computer program product of claim 14, wherein the physiological signal is a signal indicative of a heart rate of the wearer.

18. The computer program product of claim 14, wherein determining the fundamental frequency includes one or more of identifying a dominant peak in the spectrum of the motion signal and identifying the fundamental frequency using at least one of a harmonic product spectrum and a complex cepstrum of the spectrum of the motion signal.

19. A system comprising:

a memory configured to store a physiological signal over time, the physiological signal indicative of a physical state of a wearer of a device for physiological monitoring, and the memory further configured to store a motion signal of the device over time; and

a server configured to filter the physiological signal based on applying a notch filter to the physiological signal, wherein the notch filter attenuates a fundamental frequency of the motion signal and one or more related frequencies of the motion signal.

20. The system of claim 19, wherein the one or more related frequencies include at least one of the following:

one or more harmonics of the fundamental frequency and a number of frequencies selected based on a physical model of the device and the wearer, the physical model including multiplicative modulation of the physiological signal and the motion signal.

21. A method for mitigating motion artifacts in a physiological signal from a wearable physiological monitoring device, the method comprising:

acquiring a physiological signal with a device over time, wherein the device is a wearable device for physiological monitoring including a physiological sensor to capture the physiological signal, and further wherein the physiological signal is indicative of a physical state of a wearer of the device;

measuring motion of the device as a motion signal over time, wherein the motion signal includes three-dimensional motion data from a three-axis motion sensing system of the device;

determining a fundamental frequency of a spectrum of the motion signal in at least one axis;

providing a model establishing a relationship between three-dimensional motion of the device and the physiological signal obtained from the physiological sensor; and

applying the model to remove a motion artifact in the physiological signal caused by the three-dimensional motion of the device based on the three-dimensional motion data from the three-axis motion sensing system.