Classification of PVC Beat in ECG Using Basic Temporal Features

Yasin KAYA

doi:https://doi.org/10.17694/bajece.419541

Article Details

Classification of PVC Beat in ECG Using Basic Temporal Features

Authors:

Yasin KAYA

Publisher:

Balkan Yayın

Main Topics:

Applied physics

Journal:

Balkan Journal of Electrical and Computer Engineering 2018 Vol.6 Issue 2, pp.78-82

Document Type:

Article

Publication Date:

4/2018

Document Language:

English

Document ID (Org No.):

2000927466

Frequency:

Quarterly

pISSN:

2147-284X

DOI:

https://doi.org/10.17694/bajece.419541

Abstract:

 


Premature ventricular contraction (PVC) is
one of the most important arrhythmias among the various hearth abnormalities. Premature
depolarization of the myocardium in the ventricular region causes PVC and it is
usually associated with
structural heart conditions. Arrhythmias can be detected by examining the ECG
signal and this review requires large-size data to be examined by physicians. The
time spent by the physician in examining the signal can be reduced using CAD
systems. In this study, we propose a high performance
PVC detection system using the feature extraction and classification scheme
bringing low computational burden. The test set consisting of 81844 beats from
the MIT-BIH arrhythmia database was used for the experimental results. We
compared the performances of the various classifiers using proposed feature set
in the experiments and obtained classification accuracy of 98.71% using NN
classifier. 

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Article Details

Classification of PVC Beat in ECG Using Basic Temporal Features

Authors: Yasin KAYA

Publisher: Balkan Yayın

Main Topics: Applied physics

Journal: Balkan Journal of Electrical and Computer Engineering 2018 Vol.6 Issue 2, pp.78-82

Document Type: Article

Publication Date: 4/2018

Document Language: English

Document ID (Org No.): 2000927466

Frequency: Quarterly

pISSN: 2147-284X

DOI: https://doi.org/10.17694/bajece.419541

Issues

Authors:

Yasin KAYA

Publisher:

Balkan Yayın

Main Topics:

Applied physics

Journal:

Balkan Journal of Electrical and Computer Engineering 2018 Vol.6 Issue 2, pp.78-82

Document Type:

Article

Publication Date:

4/2018

Document Language:

English

Document ID (Org No.):

2000927466

Frequency:

Quarterly

pISSN:

2147-284X

DOI:

https://doi.org/10.17694/bajece.419541