DETERMINING CARDIAC ARRHYTHMIA FROM A VIDEO OF A SUBJECT BEING MONITORED FOR CARDIAC FUNCTION

• US 20130345569A1
• Filed: 06/25/2012
• Published: 12/26/2013
• Est. Priority Date: 06/25/2012
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: MESTHA, Lalit Keshav, XU, Beilei, AUSTIN, Paul R.
• Granted Patent: US 8,768,438 B2
• Time in Patent Office: Days
• US Class Current: 600/473
• CPC Class Codes: A61B 5/0044 for the heart
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle

Abstract

What is disclosed is a system and method for processing a time-series signal generated by video images captured of a subject of interest in a non-contact, remote sensing environment such that the existence of a cardiac arrhythmia can be determined for that subject. In one embodiment, a time-series signal generated is received. The time-series signal was generated from video images captured of a region of exposed skin where photoplethysmographic (PPG) signals of a subject of interest can be registered. Signal separation is performed on the time-series signal to extract a photoplethysmographic signal for the subject. Peak-to-peak pulse points are detected in the PPG signal using an adaptive threshold technique with successive thresholds being based on variations detected in previous magnitudes of the pulse peaks. The pulse points are then analyzed to obtain peak-to-peak pulse dynamics. The existence of cardiac arrhythmias is determined for the subject based on the pulse dynamics.

Claims

1. A method for detecting cardiac arrhythmia from signals generated from video images captured of a subject of interest being monitored for cardiac function in a non-contact remote sensing environment, the method comprising:

receiving a time-series signal generated from video images captured of a region of exposed skin where a photoplethysmographic (PPG) signal of a subject of interest can be registered, said video comprising video images captured by at least one imaging channel capturing PPG signals;

performing signal separation on said time-series signal to extract a PPG signal for said subject;

detecting peak-to-peak pulse points in said PPG signal;

analyzing said pulse points to obtain peak-to-peak pulse dynamics; and

determining whether a cardiac arrhythmia exists based on said pulse dynamics.

2. The method of claim 1, wherein said video images comprise any combination of:

NIR images, RGB images, RGB with NIR images, multispectral images, and hyperspectral video images.

3. The method of claim 1, wherein, in advance of obtaining said time-series signal, pre-processing said video to compensate for any of:

a motion induced blur, an imaging blur, and slow illuminant variation.

4. The method of claim 1, wherein performing signal separation on said time-series signal comprises performing, using a reference signal, a constrained source separation algorithm on said time-series signal to obtain said PPG signal.

5. The method of claim 4, wherein said reference signal has a frequency range that approximates a frequency range of said subject'"'"'s cardiac pulse.

6. The method of claim 1, wherein said peak-to-peak pulse points are detected in said PPG signal using an adaptive threshold technique with successive thresholds being based on variations detected in previous magnitudes of said pulse peaks.

7. The method of claim 1, further comprising pre-processing said time-series signal by upsampling said signal to a standard sampling frequency in order to enhance the accuracy of detecting said peak-to-peak pulse points.

8. The method of claim 1, wherein said cardiac arrhythmia is determined using a Poincare diagram of said peak-to-peak pulse dynamics, said Poincare diagram showing a relationship between consecutive beats.

9. The method of claim 1, wherein, in advance of detecting said peak-to-peak pulse points, further comprising filtering said signal using a moving average comprising:

10. The method of claim 1, further comprising normalizing said detected peak-to-peak pulse points to a frequency of 60 bpm to reduce pulse variations in said PPG signal.

11. The method of claim 1, wherein determining a cardiac arrhythmia comprises determining whether a time interval between consecutive peaks in said PPG signal is outside an acceptable limit for said subject.

12. The method of claim 1, wherein said time-series signal comprises one of:

stored values, and values generated from a streaming video.

13. The method of claim 1, further comprising comparing said subject'"'"'s peak-to-peak pulse dynamics across different patients.

14. The method of claim 1, further comprising communicating said subject'"'"'s peak-to-peak pulse dynamics to a display device.

15. A system for detecting cardiac arrhythmia from signals generated from video images captured of a subject of interest being monitored for cardiac function in a non-contact remote sensing environment, the system comprising:

a display device; and

a processor in communication with a memory, said processor executing machine readable instructions for performing;

receiving a time-series signal generated from video images captured of a region of exposed skin where a photoplethysmographic (PPG) signal of a subject of interest can be registered, said video comprising video images captured by at least one imaging channel capturing PPG signals;

performing signal separation on said time-series signal to extract a PPG signal for said subject;

detecting peak-to-peak pulse points in said PPG signal;

analyzing said pulse points to obtain peak-to-peak pulse dynamics;

determining whether a cardiac arrhythmia exists based on said pulse dynamics; and

communicating said pulse dynamics to said display device.

16. The system of claim 15, wherein said video images comprise any combination of:

NIR images, RGB images, RGB with NIR images, multispectral images, and hyperspectral video images.

17. The system of claim 15, wherein, in advance of obtaining said time-series signal, pre-processing said video to compensate for any of:

a motion induced blur, an imaging blur, and slow illuminant variation.

18. The system of claim 15, wherein performing signal separation on said time-series signal comprises performing, using a reference signal, a constrained source separation algorithm on said time-series signal to obtain said PPG signal.

19. The system of claim 18, wherein said reference signal has a frequency range that approximates a frequency range of said subject'"'"'s cardiac pulse.

20. The system of claim 15, wherein said peak-to-peak pulse points are detected in said PPG signal using an adaptive threshold technique with successive thresholds being based on variations detected in previous magnitudes of said pulse peaks.

21. The system of claim 15, further comprising pre-processing said time-series signal by upsampling said signal to a standard sampling frequency in order to enhance the accuracy of detecting said peak-to-peak pulse points.

22. The system of claim 15, wherein said cardiac arrhythmia is determined using a Poincare diagram of said peak-to-peak pulse dynamics, said Poincare diagram showing a relationship between consecutive beats.

23. The system of claim 15, wherein, in advance of detecting said peak-to-peak pulse points, further comprising filtering said signal using a moving average comprising:

24. The system of claim 15, further comprising normalizing said detected peak-to-peak pulse points to a frequency of 60 bpm to reduce pulse variations in said PPG signal.

25. The system of claim 15, wherein determining a cardiac arrhythmia comprises determining whether a time interval between consecutive peaks in said PPG signal is outside an acceptable limit for said subject.