METHOD AND APPARATUS FOR CARDIAC ARRHYTHMIA CLASSIFICATION USING SAMPLE ENTROPY

• US 20090118630A1
• Filed: 01/06/2009
• Published: 05/07/2009
• Est. Priority Date: 06/13/2005
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Li, Dan
• Granted Patent: US 8,825,146 B2
• Time in Patent Office: Days
• US Class Current: 600/518
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• 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: G06F 2218/08 Feature extraction
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

An implantable medical device includes an arrhythmia detection and classification system that classifies an arrhythmia episode based on an irregularity parameter and/or a complexity parameter. The arrhythmia episode is detected from a cardiac signal. The irregularity parameter is indicative of the degree of cycle length irregularity of the cardiac signal and the complexity parameter is indicative of the degree of morphological complexity of the cardiac signal. One example of the irregularity parameter is an irregularity sample entropy, or a parameter related to the irregularity sample entropy, computed to indicate the cycle length irregularity. One example of the complexity parameter is a complexity sample entropy, or a parameter related to the complexity sample entropy, computed to indicate the morphological complexity. In one embodiment, the detected arrhythmia episode is classified using both the irregularity parameter and the complexity parameter.

Claims

1. A system for classifying cardiac arrhythmias, the system comprising:

a signal input to receive a cardiac signal indicative of a detected arrhythmia episode;

at least one of an irregularity analyzer and a complexity analyzer, coupled to the signal input, the irregularity analyzer including an irregularity entropy computer adapted to compute an irregularity parameter Γ

_I related to an irregularity sample entropy (SampEn_I) indicative of the cycle length irregularity of the cardiac signal, wherein SampEn_I=−

InΓ

_I, the complexity analyzer including a complexity entropy computer adapted to compute a complexity parameter Γ

_C related to a complexity sample entropy (SampEn_C) indicative of the morphological complexity of the cardiac signal, wherein SampEn_C=−

InΓ

_C; and

an arrhythmia classifier coupled to the irregularity analyzer and the complexity analyzer, the arrhythmia classifier adapted to classify the detected arrhythmia episode using at least one of the irregularity parameter and the complexity parameter.

2. The system of claim 1, comprising the irregularity analyzer.

3. The system of claim 2, wherein the arrhythmia classifier comprises an irregularity comparator adapted to compare Γ

_I to a predetermined irregularity threshold (γ

_I) and indicate a detection of irregularity if Γ

_I is below γ

_I, and is adapted to classify the detected arrhythmia episode as fibrillation if the detection of irregularity is indicated and to classify the detected arrhythmia episode as tachycardia if the detection of irregularity is not indicated.

4. The system of claim 2, wherein the irregularity entropy computer is further adapted to compute SampEn_I using Γ

_I, and wherein the arrhythmia classifier comprises an irregularity comparator adapted to compare SampEn_I to a predetermined irregularity entropy threshold (θ

_I) and indicate a detection of irregularity if SampEn_I exceeds θ

_I, and is adapted to classify the detected arrhythmia episode as fibrillation if the detection of irregularity is indicated and to classify the detected arrhythmia episode as tachycardia if the detection of irregularity is not indicated.

5. The system of claim 1, comprising the complexity analyzer.

6. The system of claim 5, wherein the complexity analyzer comprises a complexity comparator adapted to compare Γ

_C to a predetermined complexity threshold (γ

_C) and indicate a detection of complexity if Γ

_C is below γ

_C, and wherein the arrhythmia classifier is adapted to classify the detected arrhythmia episode as fibrillation if the detection of complexity is indicated and to classify the detected arrhythmia episode as tachycardia if the detection of complexity is not indicated.

7. The system of claim 5, wherein the complexity entropy computer is further adapted to compute SampEn_C using Γ

_C, and wherein the arrhythmia classifier comprises an complexity comparator adapted to compare SampEn_C to a predetermined complexity entropy threshold (θ

_C) and indicate a detection of complexity if SampEn_C exceeds θ

_C, and is adapted to classify the detected arrhythmia episode as fibrillation if the detection of complexity is indicated and to classify the detected arrhythmia episode as tachycardia if the detection of complexity is not indicated.

8. The system of claim 1, comprising the irregularity analyzer and the complexity analyzer.

9. The system of claim 8, wherein the arrhythmia classifier comprises:

an irregularity comparator adapted to compare Γ

_I to a predetermined irregularity threshold (γ

_I) and indicate a detection of irregularity Γ

_I is below γ

_I; and

a complexity comparator adapted to compare Γ

_C to a predetermined complexity threshold (γ

_C) and indicate a detection of complexity if Γ

_C is below γ

_C, and

wherein the arrhythmia classifier is adapted to classify the detected arrhythmia episode as fibrillation if at least one of the detection of irregularity and the detection of complexity is indicated and to classify the detected arrhythmia episode as tachycardia if none of the detection of irregularity and the detection of complexity is indicated.

10. The system of claim 8, wherein the irregularity entropy computer is further adapted to compute SampEn_I using Γ

_I, wherein the complexity entropy computer is further adapted to compute SampEn_C using Γ

_C, and wherein the arrhythmia classifier comprises an irregularity comparator adapted to compare SampEn_I to a predetermined irregularity entropy threshold (θ

_I) and indicate a detection of irregularity if SampEn_I exceeds θ

_I and a complexity comparator adapted to compare SampEn_C to a predetermined complexity entropy threshold (θ

_C) and indicate a detection of complexity if SampEn_C exceeds θ

_C, and is adapted to classify the detected arrhythmia episode as fibrillation if at least one of the detection of irregularity and the detection of complexity is indicated and to classify the detected arrhythmia episode as tachycardia if none of the detection of irregularity and the detection of complexity is indicated.

11. A method for classifying cardiac arrhythmias, the method comprising:

detecting an arrhythmia episode;

receiving a cardiac signal indicative of the arrhythmia episode;

computing at least one of an irregularity parameter and a complexity parameter, the irregularity parameter being an irregularity parameter Γ

_I related to an irregularity sample entropy (SampEn_I) indicative of the cycle length irregularity of the cardiac signal, wherein SampEn_I=−

InΓ

_I, the complexity parameter being a complexity parameter Γ

_C related to a complexity sample entropy (SampEn_C) indicative of the morphological complexity of the cardiac signal, wherein SampEn_C=−

InΓ

_C; and

classifying the arrhythmia episode using at least one of the irregularity parameter and the complexity parameter.

12. The method of claim 11, comprising:

computing Γ

_I; and

classifying the arrhythmia episode using Γ

_I.

13. The method of claim 12, comprising:

comparing Γ

_I to a predetermined irregularity threshold (γ

_I);

indicating a detection of irregularity if Γ

_I is below γ

_I; and

classifying the arrhythmia episode as fibrillation if the detection of irregularity is indicated and as tachycardia if the detection of irregularity is not indicated.

14. The method of claim 12, wherein classifying the arrhythmia episode comprises:

computing SampEn_I using Γ

_I;

comparing SampEn_I to a predetermined irregularity entropy threshold (θ

_I);

indicating a detection of irregularity if SampEn_I exceeds θ

_I; and

classifying the arrhythmia episode as fibrillation if the detection of irregularity and is indicated and as tachycardia if the detection of irregularity is not indicated.

15. The method of claim 11, comprising:

computing Γ

_C; and

classifying the arrhythmia episode using Γ

_C.

16. The method of claim 15, comprising:

comparing Γ

_C to a predetermined complexity threshold (γ

_C);

indicating a detection of irregularity if Γ

_C is below γ

_C; and

classifying the arrhythmia episode as fibrillation if the detection of complexity is indicated and as tachycardia if the detection of complexity is not indicated.

17. The method of claim 15, wherein classifying the arrhythmia episode comprises:

computing SampEn_C using Γ

_C;

comparing SampEn_C to a predetermined complexity entropy threshold (θ

_C);

indicating a detection of complexity if SampEn_I exceeds θ

_C; and

classifying the arrhythmia episode as fibrillation if the detection of complexity and is indicated and as tachycardia if the detection of complexity is not indicated.

18. The method of claim 11, comprising:

computing Γ

_I and Γ

_C; and

classifying the arrhythmia episode using Γ

_I and γ

_C.

19. The method of claim 18, comprising:

comparing Γ

_I to a predetermined irregularity threshold (γ

_I);

indicating a detection of irregularity if Γ

_I is below γ

_I;

comparing Γ

_C to a predetermined complexity threshold (γ

_C);

indicating a detection of irregularity if Γ

_C is below γ

_C; and

classifying the arrhythmia episode as fibrillation if at least one of the detection of irregularity and the detection of complexity is indicated and as tachycardia if none of the detection of irregularity and the detection of complexity is indicated.

20. The method of claim 18, wherein classifying the arrhythmia episode comprises:

computing SampEn_I using Γ

_I;

comparing SampEn_I to a predetermined irregularity entropy threshold (θ

₁);

indicating a detection of irregularity if SampEn_I exceeds θ

_I;

computing SampEn_C using Γ

_C;

comparing SampEn_C to a predetermined complexity entropy threshold (θ

_C);

indicating a detection of complexity if SampEn_I exceeds θ

_C; and

classifying the arrhythmia episode as fibrillation if at least one of the detection of irregularity and the detection of complexity is indicated and as tachycardia if none of the detection of irregularity and the detection of complexity is indicated.