Atrial Fibrillation Classification Using Power Measurement

• US 20130197380A1
• Filed: 01/10/2013
• Published: 08/01/2013
• Est. Priority Date: 01/10/2012
• Status: Active Grant

• Current Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Original Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Inventors: Oral, Hakan, Berenfeld, Omer, Kruger, Grant
• Granted Patent: US 9,037,223 B2
• Time in Patent Office: Days
• US Class Current: 600/518
• CPC Class Codes: A61B 5/30 Input circuits therefor
• 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 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61N 1/3956 Implantable devices for applying electric shocks to the heart, e.g. for cardioversion
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

An atrial fibrillation classification system collects celectrocardiogram signals and converts them to a frequency, time, or phase domain representation for analysis. An evaluation stage extracts energy density profile over a range of frequencies, time intervals, or phases, which is then summed and normalized to form dispersion metrics. The system then analyzes the dispersion metrics, in their respective domains, to determine whether a patient is experiencing an arrhythmia and then to classify the type of arrhythmia being experienced.

Claims

1. An apparatus for detecting arrhythmias within a body, the apparatus comprising:

an input stage to receive an electrocardiogram signal from a body connected thereto through a detection electrode input, wherein the input stage is a real-time dynamically adjustable signal transformation stage configured to condition the electrocardiogram signal;

an analysis stage coupled to the input stage to receive the conditioned electrocardiogram signal from the input stage, wherein the analysis stage comprises,

a transformation stage wherein a frequency, time, or phase domain representation of the conditioned electrocardiogram signal is formed from the conditioned electrocardiogram signal being in a time-domain signal, and

an evaluation stage, wherein frequency, time or phase domain features related to the arrhythmias are extracted from the frequency, time, or phase domain representation, wherein the evaluation stage is configured to determine a summed energy over a predetermined range of frequencies, time intervals or phases for the frequency, time, or phase domain representation and configured to normalize the summed energy to form a spectral frequency dispersion metric (SFDM), spectral time domain dispersion metric (STDM), and/or spectral phase domain dispersion metric (SPDM) over the predetermined range of frequencies, time intervals, or phases; and

a classification stage coupled to the evaluation stage to receive the SFDM, STDM, and/or SPDM and to determine whether the body is experiencing the arrhythmias.

2. The apparatus of claim 1, wherein the arrhythmias comprise atrial fibrillation, ventricular fibrillation, atrial flutter, or other arrhythmia.

3. The apparatus of claim 1, wherein the input stage is configured to condition the electrocardiogram signal by filtering, amplifying, and/or digitizing the electrocardiogram signal.

4. The apparatus of claim 1, wherein the transformation stage further includes:

a buffering sub-stage for buffering the conditioned electrocardiogram signal;

a Fourier transform sub-stage coupled to the buffering stage for converting the buffered electrocardiogram signal into a Fourier domain signal; and

a filtering stage to select certain frequencies or bands of frequencies of the buffered electrocardiogram signal.

5. The apparatus of claim 4, wherein the buffering sub-stage comprises an averaging sub-stage and an offset sub-stage, wherein the averaging sub-stage accumulates electrocardiogram signals over a buffer time window and averages the accumulated electrocardiogram signals.

6. The apparatus of claim 1, wherein the evaluation stage is configured to perform multiple feature extractions over time and produce statistics metrics for the SFDM, STDM and/or SPDM prior to classification at the classification stage.

7. The apparatus of claim 1, wherein the evaluation stage is configured to determine at least one of a mean, standard deviation, a skewness and a kurtosis of the SFDM, STDM and/or SPDM.

8. The apparatus of claim 7, wherein the classification stage is coupled to the evaluation stage to determine whether the body is experiencing sinus rhythm, atrial fibrillation, atrial flutter or ventricular fibrillation based on the SFDM and at least one of the standard deviation of the SFDM distribution, the skewness of the SFDM distribution, or the kurtosis of the SFDM distribution.

9. The apparatus of claim 1, wherein the frequency, time, and/or phase domain representations is a frequency domain representation, composed of a weighted group of frequencies.

10. The apparatus of claim 1, wherein the frequency, time, and/or phase domain representation is a phase domain representation.

11. The apparatus of claim 1, wherein the frequency, time, and/or phase domain representation of the conditioned electrocardiogram signal is composed of a weighted group of phase-delays.

12. The apparatus of claim 1, wherein the input stage and the analysis stage are spatially separated from one another and connected through a wireless communication medium.

13. The apparatus of claim 1, wherein the analysis stage is coupled to the input stage to statically or dynamically adjust, in real-time, the conditioning of the electrocardiogram signal in the input stage.

14. The apparatus of claim 1, wherein the predetermined range of frequencies is between 0-100 Hz.

15. The apparatus of claim 1, wherein the predetermined range of frequencies is between 0-40 Hz.

16. The apparatus of claim 1, wherein the predetermined range of frequencies is between 3-20 Hz.

17. The apparatus of claim 1, wherein the evaluation stage is configured to,

determine a summed energy value for the predetermined range of frequencies, and

normalize that summed energy value to the energy at the frequency within the predetermined range of frequencies having the maximum energy, to determine the SFDM.

18. The apparatus of claim 1, wherein the evaluation stage is to utilize different portions of the frequency, time, and/or phase domain representation sets to distinguish between sinus rhythm, atrial fibrillation, atrial flutter and/or ventricular fibrillation.

19. The apparatus of claim 1, wherein the evaluation stage uses a search algorithm to automatically determine from the electrocardiogram signal optimal sets of frequencies to use in distinguishing between sinus rhythm, atrial fibrillation, atrial flutter and/or ventricular fibrillation.

20. The apparatus of claim 19, wherein the search algorithm is a genetic algorithm.

21. The apparatus of claim 1, wherein the evaluation stage is to determine a maximum spectrum spread difference between sinus rhythm, atrial fibrillation, atrial flutter, and/or ventricular fibrillation from identified discrete frequency components of the frequency, time, and/or phase domain representation within the range of frequencies.

22. The apparatus of claim 1, wherein the classification stage accesses a stored plurality of SFDM ranges each corresponding to a different arrhythmia, the classification stage being configured to compare the SFDM received from the evaluation stage to the stored plurality of SFDM ranges to determined the type of arrhythmia experienced by the body.

23. The apparatus of claim 1, wherein the classification stage receives a single feature or vector of transformed features from the transformed time-domain or frequency-domain signal.

24. The apparatus of claim 1, wherein the input stage is an analog conditioning circuit.

25. The apparatus of claim 24, wherein the analysis stage is a digital circuit coupled to the analog conditioning circuit to sample the conditioned electrocardiogram signal at a sampling rate.

26. The apparatus of claim 1, wherein apparatus is an implantable device.

27. The apparatus of claim 26, wherein the implantable device is contained within an implantable cardiac defibrillator device for detection of ventricular fibrillation and to control delivery of fibrillation therapy.

28. The apparatus of claim 1, wherein the apparatus is contained within an automated internal or external defibrillator for detection of ventricular fibrillation and to control delivery of fibrillation therapy.

29. The apparatus of claim 1, further comprising:

a memory for storing electrocardiogram signal data, SFDM, STDM, and/or SPDM data, and a classification determination data; and

a wireless transceiver to automatically transmit the electrocardiogram signal data, the SFDM, STDM, and/or SPDM data, and the classification determination data to a remote server through a wireless communication medium.

30. The apparatus of claim 1, further comprising:

a learning engine configured to receive an AF classification determination from the classification stage; and

a sensitivity and specificity engine coupled to the learning engine, wherein in response to a control signal from the learning engine, the sensitivity and specificity engine adjusts the sensitivity and/or specificity of the classification stage.

31. The apparatus of claim 1, further comprising:

a user input interface to receive an AF classification determination from the classification stage; and

a sensitivity and specificity engine coupled to the user input interface, wherein in response to a control signal from the user input interface, the sensitivity and specificity engine adjusts the sensitivity and/or specificity of the classification stage.

32. An apparatus for detecting arrhythmias within a body, the apparatus comprising:

an input stage to receive an electrocardiogram signal from a body connected thereto through a detection electrode input, wherein the input stage is a real-time dynamically adjustable signal transformation stage configured to condition the electrocardiogram signal;

an analysis stage coupled to the input stage to receive the conditioned electrocardiogram signal from the input stage, wherein the analysis stage comprises,

a transformation stage wherein a time domain profile of the conditioned electrocardiogram signal is formed, and

an evaluation stage configured to determine, over the time domain profile, at a plurality of predetermined time intervals, the number of times a spectral time domain dispersion metric (STDM) is in one or more count ranges over the plurality of predetermined time intervals, wherein the count ranges correspond to one or more arrhythmias; and

a classification stage coupled to the evaluation stage to receive the STDM and to determine whether the body is experiencing the arrhythmias.

33. The apparatus of claim 32, wherein the time domain profile is a histogram.

34. The apparatus of claim 32, wherein the arrhythmias comprises atrial fibrillation, ventricular fibrillation, atrial flutter, or another arrhythmia.

35-43. -43. (canceled)