An arrhythmia classification system based on the RR-interval signal.

M G Tsipouras; D I Fotiadis; D Sideris

doi:10.1016/j.artmed.2004.03.007

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An arrhythmia classification system based on the RR-interval signal.

M G Tsipouras·D I Fotiadis·D Sideris

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Abstract

OBJECTIVE: This paper proposes a knowledge-based method for arrhythmic beat classification and arrhythmic episode detection and classification using only the RR-interval signal extracted from ECG recordings. METHODOLOGY: A three RR-interval sliding window is used in arrhythmic beat classification algorithm. Classification is performed for four categories of beats: normal, premature ventricular contractions, ventricular flutter/fibrillation and 2 degrees heart block. The beat classification is used as input of a knowledge-based deterministic automaton to achieve arrhythmic episode detection and classification. Six rhythm types are classified: ventricular bigeminy, ventricular trigeminy, ventricular couplet, ventricular tachycardia, ventricular flutter/fibrillation and 2 degrees heart block. RESULTS: The method is evaluated by using the MIT-BIH arrhythmia database. The achieved scores indicate high performance: 98% accuracy for arrhythmic beat classification and 94% accuracy for arrhythmic episode detection and classification. CONCLUSION: The proposed method is advantageous because it uses only the RR-interval signal for arrhythmia beat and episode classification and the results compare well with more complex methods.

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Algorithms Arrhythmias, Cardiac Artificial Intelligence Bundle-Branch Block Databases as Topic Electrocardiography Heart Rate Humans Neural Networks, Computer Predictive Value of Tests Sensitivity and Specificity Signal Processing, Computer-Assisted Tachycardia, Ventricular Ventricular Fibrillation Ventricular Premature Complexes Comparative Study Journal Article

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M G Tsipouras, D I Fotiadis, D Sideris. 2005. An arrhythmia classification system based on the RR-interval signal.. https://doi.org/10.1016/j.artmed.2004.03.007

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