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Characterization of ventricular arrhythmias using a semantic mining algorithm

Othman, Mohd. Afzan and Mat Safri, Norlaili (2012) Characterization of ventricular arrhythmias using a semantic mining algorithm. Journal of Mechanics in Medicine and Biology, 12 (3). pp. 1250049-1. ISSN 0219-5194

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Official URL: https://dx.doi.org/10.1142/S0219519412004946


Ventricular arrhythmia, especially ventricular fibrillation, is a type of arrhythmia that can cause sudden death. The aim of this paper is to characterize ventricular arrhythmias using semantic mining by extracting their significant characteristics (frequency, damping coefficient and input signal) from electrocardiogram (ECG) signals that represent the biological behavior of the cardiovascular system. Real data from an arrhythmia database are used after noise filtering and were statistically classified into two groups; normal sinus rhythm (N) and ventricular arrhythmia (V). The proposed method achieved high sensitivity and specificity (98.1% and 97.7%, respectively) and was capable of describing the differences between the N and V types in the ECG signal.

Item Type:Article
Uncontrolled Keywords:Biology
Subjects:Q Science > QH Natural history
Divisions:Electrical Engineering
ID Code:46687
Deposited By: Haliza Zainal
Deposited On:22 Jun 2015 13:56
Last Modified:18 Sep 2017 11:43

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