System, method and computer program product for detection of changes in health status and risk of imminent illness

• US 8,588,908 B2
• Filed: 02/04/2009
• Issued: 11/19/2013
• Est. Priority Date: 02/04/2008
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Moorman, J. Randall, Lake, Douglas E.
• Primary Examiner(s): Holmes, Rex R
• Application Number:
  US12/866,056
• Publication Number:
  US 20100324436A1
• Time in Patent Office: 1,749 Days
• Field of Search: 607/5, 607/14, 607/18, 607 25- 26, 600508-509, 600/518
• US Class Current: 607/14
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/339 Displays specially adapted therefor
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis

Abstract

A method for analysis of cardiac rhythm and RR interval time series based on entropy related data and entropy based measures. The information is related to but distinct from entropy, and is derived from histograms of interval match counts in which the y-axis is the frequency of intervals of length in that have the match count given on the x-axis. The phenotype of the histogram informs on the presence of atrial fibrillation or, in the presence of sinus rhythm, the degree of congestive heart failure.

Claims

1. A method of detecting abnormal cardiac rhythms and clinical status of a subject comprising:

obtaining physiological data obtained from a sampling device from the subject comprising one or more series of intervals;

calculating entropy related data using a computer processing device configured for processing the physiological data based on the one or more series of intervals, wherein the entropy related data are new entropy based measures of time series comprising;

interval match count histograms, and

histogram derived measures in which the y-axis of the histograms is the frequency of intervals of length m that have the match count given on the x-axis; and

generating a diagnostic output based on the entropy related data.

2. The method of claim 1, wherein generating the diagnostic output comprises using a regression model to combine the numbers of matching intervals.

3. The method of claim 1, wherein the physiological data comprises two or more series of intervals obtained simultaneously from different physiological signals.

4. The method of claim 1 further comprising separating the one or more series of intervals into a plurality of subsets of the one or more series of intervals.

5. The method of claim 4, wherein calculating the entropy related data further comprises averaging entropy related data from each of the plurality of the subsets of the one or more series of intervals.

6. The method of claim 4, wherein the subsets of the one or more series of intervals comprise less than 13 intervals.

7. The method of claim 1, wherein generating the diagnostic output further comprises using coefficient of sample entropy (COSEn).

8. The method of claim 1 further comprising producing an output to a medical care provider to diagnose abnormal cardiac rhythms and clinical status of the subject.

9. The method of claim 1, wherein the one or series of intervals comprises a number of samples during one period of a cardiac rhythm.

10. The method of claim 1, wherein calculating entropy related data based on the interval match count histograms further comprises a tolerance value (r) for determining whether two or more intervals match.

11. The method of claim 9, wherein the data from the cardiac rhythm of a subject comprises samples from an EKG waveform.

12. The method of claim 1, further comprising calculating an absolute entropy measurement.

13. The method of claim 12, wherein the absolute entropy measurement is a coefficient of sample entropy (COSEn).

14. An apparatus for detecting abnormal cardiac rhythms and clinical status of a subject comprising:

a sampling device for obtaining physiological data from the subject comprising a one or more series of intervals;

a computer processing device configured for processing the physiological data from the subject into entropy related data and producing a diagnostic result, wherein the entropy related data are new entropy based measures of time series comprising;

interval match count histograms, and

histogram derived measures in which the y-axis of the histograms is the frequency of intervals of length m that have the match count given on the x-axis; and

an result device for rendering the diagnostic output.

15. The apparatus of claim 14, wherein the sampling device comprises an EKG machine.

16. The apparatus of claim 14, wherein producing the diagnostic result comprises running a regression model on the entropy related data.

17. The apparatus according to claim 14, wherein the physiological data is representative of a cardiac rhythm and clinical status of the subject.