Application of ECG Arrhythmia Classification by Means of Bayesian Theorem

The electrocardiogram (ECG) is a vital signal to investigate the heart functional, it is one of the most important electrical signals which characterize human heart performance and gives a fast anticipation about the heart condition. The main objective of this study is to use the Bayesian algorithm...

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Bibliographic Details
Published inJournal of applied sciences (Asian Network for Scientific Information) Vol. 14; no. 2; p. 165
Main Authors Alturki, Alaa M, Al-Ghamdi, Abdulaziz M, Daqrouq, Khaled, Al-Hmouz, Rami
Format Journal Article
LanguageEnglish
Published 01.01.2014
Subjects
Algorithms
Arrhythmia
Bayesian analysis
Classification
Classifiers
Feature extraction
Heart
Human
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Summary:The electrocardiogram (ECG) is a vital signal to investigate the heart functional, it is one of the most important electrical signals which characterize human heart performance and gives a fast anticipation about the heart condition. The main objective of this study is to use the Bayesian algorithm in application of ECG arrhythmia classification. The investigation of the better performance of the classifier by feature extraction methods analysis is considered. The obtained results showed that Bayesian classifier achieved with Wavelet Packet Energy (WPE) a higher success rate (93.75%). Same methods are used to check the classifier possibility when the signals are contaminated with natural noise taken from other noisy ECG signals after filtration; the obtained results showed that WPE is more appropriate for classification of ECG arrhythmia by means of Bayesian algorithm classifier, 72.13% for 0 SNR and 84.98% for 5 SNR.
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ISSN:1812-5654
1812-5662
DOI:10.3923/jas.2014.165.170