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Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 2 | Page No.: 165-170
DOI: 10.3923/jas.2014.165.170
 
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Application of ECG Arrhythmia Classification by Means of Bayesian Theorem

Alaa M. Alturki, Abdulaziz M. Al-Ghamdi, Khaled Daqrouq and Rami Al-Hmouz

Abstract:
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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How to cite this article:

Alaa M. Alturki, Abdulaziz M. Al-Ghamdi, Khaled Daqrouq and Rami Al-Hmouz , 2014. Application of ECG Arrhythmia Classification by Means of Bayesian Theorem. Journal of Applied Sciences, 14: 165-170.

DOI: 10.3923/jas.2014.165.170

URL: https://scialert.net/abstract/?doi=jas.2014.165.170

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