FREQUENCY DOMAIN PROJECTION ALGORITHM

• US 20160051157A1
• Filed: 08/22/2014
• Published: 02/25/2016
• Est. Priority Date: 08/22/2014
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: WAYDO, Stephen J.
• Granted Patent: US 10,201,286 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 5/721 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 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity

Abstract

An algorithm for determining heart rate by removing motion artifacts from a PPG signal in the frequency domain utilizes a principal component analysis. Some examples of the present disclosure process PPG signals in combination with accelerometer signals to remove unwanted artifacts in the frequency domain. For example, principal components of the accelerometer signal can be generated and combined with the PPG signal to filter out acceleration contributions represented in the PPG signal to reveal heart rate peaks. Additionally, in some examples, templates may be stored for correlation with candidate heart rate peaks to select those peaks with the highest correlations with the stored templates.

Claims

1. A device for predicting heart rate (HR), comprising:

a first sensor configured to generate raw HR signals;

a second sensor configured to generate acceleration signals along at least a first direction; and

processing circuitry capable of;

generating a frequency domain (FD) representation of the raw HR signals to provide a FD raw HR signal waveform;

generating a FD representation of the acceleration signals to provide a FD acceleration signal waveform along the first direction;

scaling a peak in the FD acceleration signal waveform at a first frequency to represent a peak at the same first frequency in the FD raw HR signal waveform;

subtracting the scaled peak of the FD acceleration signal waveform from the FD raw HR signal waveform to obtain a FD projected HR signal waveform;

selecting the frequency corresponding to the maximum peak of the FD projected HR signal waveform; and

predicting a HR based on the selected frequency.

2. The device of claim 1, wherein the processing circuitry is further capable of:

correlating the FD projected HR signal waveform with a plurality of spectral heart rate templates to generate a plurality of correlation values; and

predicting a heart rate based on the selected frequency and the plurality of correlation values.

3. The device of claim 1, wherein the processing circuitry is further capable of:

generating groups of raw HR signals and acceleration signals such that the FD raw HR signal waveforms and the FD acceleration signal waveforms are based on discrete Fourier transforms of the groups of raw HR signals and acceleration signals; and

dynamically adjusting the size of the groups in response to at least the selected frequency and previously selected frequencies.

4. A device for predicting heart rate (HR), comprising:

a first sensor configured to generate time domain raw HR signals;

a second sensor configured to generate time domain acceleration signals along first, second and third directions; and

processing circuitry capable of;

performing a principal component analysis of the time domain acceleration signals along the first, second and third directions to provide time domain principal components acceleration waveforms of the time domain acceleration signals having scores along the principal component axes PC1 and PC2;

generating a frequency domain (FD) representation of the time domain raw HR signals to provide a FD raw HR signal waveform;

generating a FD representation of the time domain principal components acceleration waveforms to provide FD acceleration signal waveforms corresponding to the principal component axes PC1 and PC2 and designating the corresponding waveforms as FD PC1 acceleration signal waveforms and FD PC2 acceleration signal waveforms respectively; and

utilizing the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms and the FD raw HR signal waveform to predict the HR.

5. The device of claim 4, wherein the processing circuitry utilizes the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms and the FD raw HR signal waveform to predict the HR by:

forming a combination of the FD PC1 and FD PC2 acceleration signal waveforms;

subtracting the combination of the FD PC1 and FD PC2 acceleration signal waveforms from the FD raw HR signal waveform to obtain a FD projected HR signal waveform;

selecting the frequency corresponding to the maximum peak of the FD projected HR signal waveform; and

predicting a HR based on the selected frequency.

6. The device of claim 4, wherein the first sensor is a photoplethysmogram (PPG) sensor and the time domain raw HR signals are time domain raw PPG signals.

7. The device of claim 5, wherein the combination of the FD PC1 and FD PC2 acceleration signal waveforms is of the form A{FD PC1 acceleration signal waveform}+B{FD PC2 acceleration signal waveform} respectively where A and B are scale factors.

8. The device of claim 7, wherein the scale factors A and B are determined by a successive approximation algorithm such as to minimize a residual value.

9. The device of claim 4, wherein the processing circuitry is further capable of:

generating groups of time domain raw HR signals and time domain acceleration signals such that the FD raw HR signal waveforms and the FD acceleration signal waveforms are based on discrete Fourier transforms of the groups of raw HR signals and acceleration signals; and

dynamically adjusting the size of the groups in response to at least the selected frequency and previously selected frequencies.

10. A device for predicting heart rate (HR), comprising:

a first sensor configured to generate time domain raw HR signals;

a second sensor configured to generate time domain acceleration signals along first, second and third directions; and

processing circuitry capable of;

performing a principal component analysis of the time domain acceleration signals along the first, second and third directions to provide time domain principal components acceleration waveforms of the time domain acceleration signals having scores along the principal component axes PC1 and PC2;

generating a frequency domain (FD) representation of the time domain raw HR signals to provide a FD raw HR signal waveform;

generating a FD representation of the time domain principal components acceleration waveforms to provide FD acceleration signal waveforms corresponding to the principal component axes PC1 and PC2 and designating the corresponding waveforms as FD PC1 acceleration signal waveforms and FD PC2 acceleration signal waveforms respectively; and

utilizing the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms, the FD raw HR signal waveform and a plurality of spectral heart rate templates to generate a plurality of correlation values to predict the HR.

11. The device of claim 10, wherein the processing circuitry utilizes the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms, the FD raw HR signal waveform and a plurality of spectral heart rate templates to generate a plurality of correlation values to predict the HR by:

forming a combination of the FD PC1 and FD PC2 acceleration signal waveforms;

subtracting the combination of the FD PC1 and FD PC2 acceleration signal waveforms from the FD raw HR signal waveform to obtain a FD projected HR signal waveform;

correlating the FD projected HR signal waveform with the plurality of spectral heart rate templates to generate the plurality of correlation values; and

predicting a heart rate based on the highest correlation value among the plurality of correlation values.

12. The device of claim 10, wherein the first sensor is a photoplethysmogram (PPG) sensor and the time domain raw HR signals are time domain raw PPG signals.

13. The device of claim 11, wherein the combination of the FD PC1 and FD PC2 acceleration signal waveforms is of the form A{FD PC1 acceleration signal waveform}+B{FD PC2 acceleration signal waveform} respectively where A and B are scale factors.

14. The device of claim 13, wherein the scale factors A and B are determined by a successive approximation algorithm such as to minimize a residual value.

15. The device of claim 10, wherein the processing circuitry is further capable of:

generating groups of time domain raw HR signals and time domain acceleration signals such that the FD raw HR signal waveforms and the FD acceleration signal waveforms are based on discrete Fourier transforms of the groups of raw HR signals and acceleration signals; and

dynamically adjusting the size of the groups in response to at least the correlation values.

16. The device of claim 15, wherein the processing circuitry is further capable of dynamically adjusting the size of the groups dependent on a currently predicted HR, a previously predicted HR and correlation values associated with the currently predicted HR and the previously predicted HR.

17. A device for adjusting a data sampling window size for processing data comprising:

a first sensor for accumulating the data during the sampling window;

processing circuitry capable of ;

determining a current value associated with the accumulated data;

comparing the determined current value with a previously determined value of the data;

adjusting the data sampling window size depending on the results of the comparison.

18. The device of claim 17, wherein the processing circuitry is capable of:

determining a confidence level associated with the determined current and previously determined values;

selecting a highest confidence level associated with the current and previously determined values; and

adjusting the data sampling window size depending on the selected confidence level.

19. A method for predicting heart rate (HR), comprising:

generating time domain raw HR signals;

generating time domain acceleration signals along first, second and third directions;

performing a principal component analysis of the time domain acceleration signals along the first, second and third directions to provide time domain principal components acceleration waveforms of the time domain acceleration signals having scores along the principal component axes PC1 and PC2;

generating a frequency domain (FD) representation of the time domain raw HR signals to provide a FD raw HR signal waveform;

generating a FD representation of the time domain principal components acceleration waveforms to provide FD acceleration signal waveforms corresponding to the principal component axes PC1 and PC2 and designating the corresponding waveforms as FD PC1 acceleration signal waveforms and FD PC2 acceleration signal waveforms respectively; and

utilizing the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms and the FD raw HR signal waveform to predict the HR.

20. The method of claim 19, further comprising:

forming a combination of the FD PC1 and FD PC2 acceleration signal waveforms;

subtracting the combination of the FD PC1 and FD PC2 acceleration signal waveforms from the FD raw HR signal waveform to obtain a FD projected HR signal waveform;

selecting the frequency corresponding to the maximum peak of the FD projected HR signal waveform; and

predicting a HR based on the selected frequency.

21. The method of claim 19, wherein the time domain raw HR signals is generated from a photoplethysmogram (PPG) sensor.

22. The method of claim 20, wherein the combination of the FD PC1 and FD PC2 acceleration signal waveforms is of the form A{FD PC1 acceleration signal waveform}+B {FD PC2 acceleration signal waveform} respectively where A and B are scale factors.

23. The method of claim 22, wherein the scale factors A and B are determined by a successive approximation algorithm such as to minimize a residual value.

24. The method of claim 19, further comprising:

generating groups of time domain raw HR signals and time domain acceleration signals such that the FD raw HR signal waveforms and the FD acceleration signal waveforms are based on discrete Fourier transforms of the groups of raw HR signals and acceleration signals; and

dynamically adjusting the size of the groups in response to at least the selected frequency and previously selected frequencies.

25. A method for predicting heart rate (HR), comprising:

generating time domain raw HR signals;

generating time domain acceleration signals along first, second and third directions;

performing a principal component analysis of the time domain acceleration signals along the first, second and third directions to provide time domain principal components acceleration waveforms of the time domain acceleration signals having scores along the principal component axes PC1 and PC2;

generating a frequency domain (FD) representation of the time domain raw HR signals to provide a FD raw HR signal waveform;

generating a FD representation of the time domain principal components acceleration waveforms to provide FD acceleration signal waveforms corresponding to the principal component axes PC1 and PC2 and designating the corresponding waveforms as FD PC1 acceleration signal waveforms and FD PC2 acceleration signal waveforms respectively; and

utilizing the FD PC1 acceleration signal waveforms, the FD PC2 acceleration signal waveforms, the FD raw HR signal waveform and a plurality of spectral heart rate templates to generate a plurality of correlation values to predict the HR.

26. The method of claim 25, further comprising:

forming a combination of the FD PC1 and FD PC2 acceleration signal waveforms;

subtracting the combination of the FD PC1 and FD PC2 acceleration signal waveforms from the FD raw HR signal waveform to obtain a FD projected HR signal waveform;

correlating the FD projected HR signal waveform with the plurality of spectral heart rate templates to generate the plurality of correlation values; and

predicting a heart rate based on the highest correlation value among the plurality of correlation values.