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Characterization of ventricular arrhythmias using a semantic mining algorithm

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) f...

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Main Authors: Othman, Mohd. Afzan, Mat Safri, Norlaili
Format: Article
Published: 2012
Subjects:
QH Natural history
Online Access:http://eprints.utm.my/id/eprint/46687/
https://dx.doi.org/10.1142/S0219519412004946
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spelling my.utm.466872017-09-18T03:43:20Z http://eprints.utm.my/id/eprint/46687/ Characterization of ventricular arrhythmias using a semantic mining algorithm Othman, Mohd. Afzan Mat Safri, Norlaili QH Natural history 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. 2012 Article PeerReviewed 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 https://dx.doi.org/10.1142/S0219519412004946 doi.org/10.1142/S0219519412004946
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QH Natural history
spellingShingle QH Natural history
Othman, Mohd. Afzan
Mat Safri, Norlaili
Characterization of ventricular arrhythmias using a semantic mining algorithm
description 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.
format Article
author Othman, Mohd. Afzan
Mat Safri, Norlaili
author_facet Othman, Mohd. Afzan
Mat Safri, Norlaili
author_sort Othman, Mohd. Afzan
title Characterization of ventricular arrhythmias using a semantic mining algorithm
title_short Characterization of ventricular arrhythmias using a semantic mining algorithm
title_full Characterization of ventricular arrhythmias using a semantic mining algorithm
title_fullStr Characterization of ventricular arrhythmias using a semantic mining algorithm
title_full_unstemmed Characterization of ventricular arrhythmias using a semantic mining algorithm
title_sort characterization of ventricular arrhythmias using a semantic mining algorithm
publishDate 2012
url http://eprints.utm.my/id/eprint/46687/
https://dx.doi.org/10.1142/S0219519412004946
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score 13.211869

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