Heart rate path optimizer

Patent metadata

Field	Value
Publication number	US-11986322-B2
Application number	US-201715848602-A
Country	US
Kind code	B2
Filing date	Dec 20, 2017
Priority date	Aug 22, 2014
Publication date	May 21, 2024
Grant date	May 21, 2024

Abstract

A device for determining a heart rate of a user has a PPG sensor and an accelerometer to compensate for acceleration artifacts within the PPG signal. The device transforms time domain PPG and accelerometer signals into the frequency domain using a Fourier transformation and utilizes the Fourier coefficient magnitudes as indicative of the probability of candidate heart rate values. Candidate heart rate values are determined at sampling times over a time interval and a most probable heart rate path during the time interval is determined using a reward/penalty algorithm.

First claim

What is claimed is:

1. A device for determining a heart rate (HR) of a user comprising:
a HR sensor configured to be worn by a user and comprising a photoplethysmogram (PPG) sensor configured to output PPG signals;
a display configured to provide a graphical output; and
a processor configured to:
sample the PPG signals over a first time period to generate a first set of data points;
determine, from the first set of data points, a first set of HR values corresponding to a first time;
select a first path of HR values in accordance with a criteria, wherein selecting the first path includes selecting a first HR value of the first set of HR values;
cause the display to display at least one of the selected first path of HR values;
sample the PPG signals over a second time period to generate a second set of data points;
determine, from the second set of data points, a second set of HR values corresponding to the second time;
select a second path of HR values in accordance with the criteria, wherein selecting the second path includes:
selecting a second HR value from the first set of HR values that is different than the first HR value in the first path of HR values; and
selecting a third HR value from the second set of HR values; and

cause the display to display at least the second HR value of the selected second path of HR values.

2. The device of claim 1 , wherein the criteria is based on consecutive Fourier coefficient magnitudes of corresponding consecutive HR values along each of the first path of HR values and the second path of HR values and differences in corresponding consecutive HR values along each of the first path of HR values and the second path of HR values.

3. The device of claim 2 , wherein the processor determines the first set of HR values by transforming the first set of data points into frequency domain HR signals (FDHR signals) and determining and adding together at least a fundamental and first harmonic of Fourier component magnitudes of the FDHR signals corresponding to the first set of data points.

4. The device of claim 3 , wherein the Fourier component magnitudes are absolute values of Fourier coefficients of the FDHR signals.

5. The device of claim 1 , wherein determining the first set of HR values includes transforming the first set of data points into frequency domain HR signals (FDHR signals) and low pass filtering Fourier component magnitudes of the FDHR signals.

6. The device of claim 5 , wherein the low pass filtering is provided by utilizing a Gaussian convolution.

7. The device of claim 1 , wherein determining the first set of HR values includes transforming the first set of data points into frequency domain HR signals (FDHR signals) and providing a peak boost to Fourier component magnitudes of the FDHR signals.

8. The device of claim 7 , wherein the peak boost multiplies each local maxima of the Fourier component magnitudes by a number larger than 1.

9. The device of claim 8 , wherein the Fourier component magnitudes are absolute values of Fourier coefficients of the FDHR signals.

10. The device of claim 1 , wherein determining the first set of HR values includes transforming the first set of data points into frequency domain HR signals (FDHR signals) and adding together at least a fundamental and first harmonic of Fourier component magnitudes of the FDHR signals corresponding to the HR signals to provide a harmonic boost and further providing a peak boost to Fourier component magnitudes of the FDHR signals by multiplying local maxima of the Fourier component magnitudes by a number larger than 1.

11. A method for determining a user's heart rate (HR) using a physiological sensing device, comprising:
detecting PPG signals using a photoplethysmogram (PPG) sensor of the physiological sensing device;
at a processor of the physiological sensing device:
sampling the PPG signals over a first time period to generate a first set of data points;
determining, from the first set of data points, a first set of HR values corresponding to a first time;
selecting a first path of HR values in accordance with a given criteria, wherein selecting the first path includes selecting a first HR value of the first set of HR values;
sampling the PPG signals over a second time period to generate a second set of data points;
determining, from the second set of data points, a second set of HR values corresponding to a second time;
selecting a second path of HR values in accordance with the given criteria, wherein selecting the second path includes:
selecting a second HR value from the first set of HR values that is different that the first HR value in the first path of HR values; and
selecting a third HR value from the second set of HR values.

12. The method of claim 11 , wherein the given criteria is based on consecutive Fourier coefficient magnitudes of corresponding consecutive HR values along each of the first path of HR values and the second path of HR values and differences in consecutive HR values along each of the first path of HR values and the second path of HR values.

13. The method of claim 12 , wherein determining the first set of HR values comprises transforming the first set of data points into frequency domain HR signals (FDHR signals) and determining and adding together at least a fundamental and first harmonic of Fourier component magnitudes of the FDHR signals corresponding to the first set of data points.

14. The method of claim 13 , wherein the Fourier component magnitudes are absolute values of Fourier coefficients of the FDHR signals.

15. The method of claim 11 , wherein determining the first set of HR values comprises transforming the first set of data points into frequency domain HR signals (FDHR signals) and low pass filtering Fourier component magnitudes of the FDHR signals.

16. The method of claim 15 , wherein the low pass filtering is provided by utilizing a Gaussian convolution.

17. The method of claim 11 , wherein determining the first set of HR values comprises transforming the HR signals into frequency domain HR signals (FDHR signals) and providing a peak boost to Fourier component magnitudes of the FDHR signals.

18. The method of claim 17 , wherein the peak boost multiplies each local maxima of the Fourier component magnitudes by a number larger than 1.

19. The method of claim 18 , wherein the Fourier component magnitudes are absolute values of Fourier coefficients of the FDHR signals.

20. The method of claim 11 , wherein determining the first set of HR values comprises transforming the first set of data points into frequency domain HR signals (FDHR signals) and adding together at least a fundamental and first harmonic of Fourier component magnitudes of the FDHR signals corresponding to the HR signals to provide a harmonic boost and further providing a peak boost to Fourier component magnitudes of the FDHR signals by multiplying local maxima of the Fourier component magnitudes by a number larger than 1.

Assignees

• Apple Inc

Inventors

• Maani Ehsan
• Culbert Daniel J
• Shapiro Ian R

Classifications

• A61B5/721 Primary

  using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured · CPC title

• A61B5/0205

  Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition · CPC title

• A61B5/024

  Measuring pulse rate or heart rate · CPC title

• A61B5/11

  Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb {(A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721)} · CPC title

• A61B5/725

  using specific filters therefor, e.g. Kalman or adaptive filters (specific diagnostics methods using using bioelectric or biomagnetic signals A61B5/316) · CPC title