Method and apparatus for detection of heartbeat characteristics

• US 9,314,181 B2
• Filed: 02/25/2015
• Issued: 04/19/2016
• Est. Priority Date: 11/03/2009
• Status: Active Grant

• Current Assignee: VivaQuant LLC
• Original Assignee: VivaQuant LLC
• Inventors: Brockway, Marina, Brockway, Brian
• Primary Examiner(s): Gedeon, Brian T
• Application Number:
  US14/630,918
• Publication Number:
  US 20150164355A1
• Time in Patent Office: 419 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/1102 Ballistocardiography
• CPC Class Codes: A61B 5/25 Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/259 using conductive adhesive means, e.g. gels
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 7/00 Instruments for auscultation
• CPC Class Codes: A61B 7/02 Stethoscopes acoustic details thereof G10K11/00
• CPC Class Codes: G06F 17/14 : Fourier, Walsh or analogous domain transformations , e.g. Laplace, Hilbert, Karhunen-Loeve, transforms for correlation function computation G06F17/156; spectrum analysers G01R23/16
• CPC Class Codes: G06F 2218/04 : Denoising
• CPC Class Codes: G06F 2218/10 : by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

Aspects of the present disclosure are directed to detecting Atrial Fibrillation (AF). As may be implemented in accordance with one or more embodiments, a time series of inter-beat intervals is computed from a recording of activity of a beating heart. The time series is decomposed into subcomponents, and an envelope of at least one of the subcomponents is computed. The presence of atrial fibrillation (AF) is detected based upon characteristics of the envelope that are indicative of AF.

Claims

1. A method comprising:

computing a time series of inter-beat intervals from a recording of activity of a beating heart;

decomposing the time series into subcomponents;

computing an envelope of at least one of the subcomponents; and

detecting the presence of atrial fibrillation (AF) based upon characteristics of the envelope that are indicative of AF.

2. The method of claim 1, wherein detecting the presence of AF based upon characteristics of the envelope that are indicative of AF includes detecting the presence of AF based upon a comparison of the envelope to a first threshold indicative of AF.

3. The method of claim 1, wherein the recording of activity includes a recording of at least one of:

an electrocardiogram;

a ballistocardiogram;

heart sounds;

blood pressure;

blood flow in an artery; and

a photoplethysmography signal of body tissue.

4. The method of claim 1, wherein computing the time series of inter-beat intervals includes:

detecting a plethora of heart beats in the recording;

identifying invalid beats from the detected beats;

computing a raw sequence of inter-beat intervals from consecutive ones of the detected beats;

creating a cleaned sequence of inter-beat intervals by excluding intervals computed using ones of the beats identified as being invalid; and

resampling said cleaned sequence of inter-beat intervals to create an equispaced time series of inter-beat intervals.

5. The method of claim 4, wherein identifying invalid beats includes identifying invalid beats based on characteristics in the recording selected from the group of:

ventricular arrhythmias;

characteristics indicating that a signal detected as a beat is not a beat; and

noise beyond a noise threshold.

6. The method of claim 4, wherein identifying invalid beats includes identifying ectopic beats by:

decomposing the recording into subcomponents,

detecting the presence of ventricular depolarizations in the subcomponents,

establishing a window around each detected ventricular depolarization,

computing the energy of high frequency and low-frequency subcomponents in each window,

computing, for each window, the ratio of low frequency energy to high frequency energy, and

detecting the presence of an ectopic beat in the window based upon the computed ratio.

7. The method of claim 6, wherein computing high frequency energy in the window includes:

selecting one or more subcomponents corresponding to high frequency, and

computing the high frequency energy using at least one of the sum of squares of the amplitude and the sum of the absolute values of the amplitude.

8. The method of claim 7, wherein computing low frequency energy in the window includes:

selecting one or more subcomponents corresponding to low frequency, and

computing low frequency energy using at least one of the sum of squares of the amplitude and the sum of the absolute values of the amplitude.

9. The method of claim 6, wherein computing low frequency energy in the window includes:

selecting one or more subcomponents corresponding to low frequency, and

computing low frequency energy using at least one of the sum of squares of the amplitude and the sum of the absolute values of the amplitude.

10. The method of claim 1, wherein computing the time series of inter-beat intervals includes:

detecting a plethora of heart beats;

identifying valid beats from the detected beats;

computing a sequence of inter-beat intervals from a series of consecutive ones of the beats, with invalid ones of the beats being excluded from the series of consecutive ones of the beats; and

resampling said sequence of inter-beat intervals to create an equispaced time series of inter-beat intervals.

11. The method of claim 1, wherein decomposing the time series into subcomponents includes applying one of the following:

a discrete cosine transform;

a stationary wavelet transform;

a discrete wavelet transform;

a filter bank;

a synchrosqueezed wavelet transform;

a Gabor transform;

a short-term Fourier transform;

a continuous wavelet transform; and

a wavelet packet transform.

12. The method of claim 1, wherein the at least one of the subcomponents includes at least one subcomponent having a frequency corresponding to a highest frequency of the subcomponents.

13. The method of claim 1, wherein detecting the presence of AF includes detecting the presence of AF based upon the envelope exceeding a first threshold for a predetermined amount of time.

14. The method of claim 13, wherein detecting the presence of AF includes detecting the presence of AF based upon:

the envelope exceeding the first threshold for the predetermined amount of time, and

a computed metric of entropy exceeding an entropy threshold.

15. The method of claim 14, further including computing the metric of entropy for at least one of:

the time series of inter-beat intervals;

a subcomponent; and

a product of subcomponents.

16. The method of claim 14, further including computing the metric of entropy using one of sample entropy and approximate entropy.

17. The method of claim 1, further including detecting an absence of AF based upon the envelope falling below a second threshold for a predetermined amount of time.

18. A method comprising:

computing a time series of inter-beat intervals from a recording of activity of a beating heart, excluding intervals characterized by ectopic beats;

decomposing the time series into subcomponents;

computing an envelope of at least one of the subcomponents; and

detecting the presence of atrial fibrillation (AF) based upon characteristics of the envelope that are indicative of AF.

19. The method of claim 18, wherein excluding intervals characterized by ectopic beats includes computing a raw sequence of inter-beat intervals from consecutive ones of detected beats in the recording, and creating a cleaned sequence of inter-beat intervals from the raw sequence of inter-beat intervals by excluding intervals computed using ones of the beats characterized as being ectopic.

20. The method of claim 18, wherein excluding intervals characterized by ectopic beats includes:

decomposing the recording into subcomponents,

detecting the presence of ventricular depolarizations in the subcomponents,

establishing a window around each detected ventricular depolarization,

computing the energy of high frequency and low-frequency subcomponents in each window, and

detecting the presence of an ectopic beat in the window based upon a ratio of energy of the low frequency components to energy of the high frequency components being indicative of the ectopic beat.

21. The method of claim 18, wherein computing the time series of inter-beat intervals includes:

detecting a plethora of heart beats in the recording;

identifying invalid beats from the detected beats as beats exhibiting ectopic characteristics;

computing a raw sequence of inter-beat intervals from consecutive ones of the detected beats;

creating a cleaned sequence of inter-beat intervals by excluding intervals computed using ones of the beats identified as being invalid; and

resampling said cleaned sequence of inter-beat intervals to create an equispaced time series of inter-beat intervals.

22. An apparatus comprising:

an input port configured and arranged for receiving a signal indicative of activity of a beating heart; and

a processing circuit configured and arranged with the input port to;

compute a time series of inter-beat intervals from a recording of activity of the beating heart;

decompose the time series into subcomponents;

compute an envelope of at least one of the subcomponents; and

detect the presence of atrial fibrillation (AF) in the received signal based upon characteristics of the envelope that are indicative of AF.

23. The apparatus of claim 22, wherein the processing circuit is configured and arranged to compute the time series of inter-beat intervals by excluding intervals characterized by ectopic beats.

24. The apparatus of claim 23, wherein the processing circuit is configured and arranged to exclude intervals characterized by ectopic beats by

computing a raw sequence of inter-beat intervals from consecutive ones of detected beats in the recording, and

creating a cleaned sequence of inter-beat intervals from the raw sequence of inter-beat intervals by excluding intervals computed using ones of the beats characterized as being ectopic.

25. The apparatus of claim 23, wherein the processing circuit is configured and arranged to exclude intervals characterized by ectopic beats by:

decomposing the recording into subcomponents,

detecting the presence of ventricular depolarizations in the subcomponents,

establishing a window around each detected ventricular depolarization,

computing the energy of high frequency and low-frequency subcomponents in each window, and

detecting the presence of an ectopic beat in the window based upon a ratio of energy of the low frequency components to energy of the high frequency components being indicative of the ectopic beat.

26. The apparatus of claim 25, wherein the processing circuit is configured and arranged to

compute the high frequency energy in the window by selecting one or more subcomponents corresponding to high frequency, and computing the high frequency energy using at least one of the sum of squares of the amplitude and the sum of the absolute values of the amplitude, and

compute the low frequency energy in the window by selecting one or more subcomponents corresponding to low frequency, and computing the low frequency energy using at least one of the sum of squares of the amplitude and the sum of the absolute values of the amplitude.

27. The apparatus of claim 22, wherein the processing circuit is configured and arranged to compute the time series of inter-beat intervals by:

detecting a plethora of heart beats in the recording;

identifying invalid beats from the detected beats;

computing a raw sequence of inter-beat intervals from consecutive ones of the detected beats;

creating a cleaned sequence of inter-beat intervals by excluding intervals computed using ones of the beats identified as being invalid; and

resampling said cleaned sequence of inter-beat intervals to create an equispaced time series of inter-beat intervals.

28. The apparatus of claim 27, wherein the processing circuit is configured and arranged to identify the invalid beats based on characteristics in the recording selected from the group of:

ventricular arrhythmias;

characteristics indicating that a signal detected as a beat is not a beat; and

noise beyond a noise threshold.

29. The apparatus of claim 22, wherein the processing circuit is configured and arranged to compute the time series of inter-beat intervals by:

detecting a plethora of heart beats;

identifying valid beats from the detected beats;

computing a sequence of inter-beat intervals from a series of consecutive ones of the beats, with invalid ones of the beats being excluded from the series of consecutive ones of the beats; and

resampling said sequence of inter-beat intervals to create an equispaced time series of inter-beat intervals.

30. The apparatus of claim 22, wherein the processing circuit is configured and arranged to detect the presence of AF in response to:

the envelope exceeding a first threshold for a predetermined amount of time, and

a computed metric of entropy.

31. A method for detecting ectopic beats in an ECG recording, the method comprising:

decomposing the recording into subcomponents;

detecting the presence of ventricular depolarizations in the subcomponents;

computing the energy of high frequency and low-frequency ones of the subcomponents in respective time windows around each ventricular depolarization; and

detecting the presence of an ectopic beat in one of the time windows based upon a ratio of energy of the low frequency components to energy of the high frequency components being indicative of the ectopic beat.