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Support vector machine based arrhythmia classification using reduced features

Authors
 Mi Hye Song  ;  Jeon Lee  ;  Sung Pil Cho  ;  Kyoung Joung Lee  ;  Sun Kook Yoo 
Citation
 INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, Vol.3(4) : 571-579, 2005 
Journal Title
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
ISSN
 1598-6446 
Issue Date
2005
MeSH
Arrhythmia classification ; linear discriminant analysis ; reduction of feature dimension ; support vector machine ; wavelet transform
Keywords
Arrhythmia classification ; linear discriminant analysis ; reduction of feature dimension ; support vector machine ; wavelet transform
Abstract
In this paper, we proposed an algorithm for arrhythmia classification, which is associated with the reduction of feature dimensions by linear discriminant analysis (LDA) and a support vector machine (SVM) based classifier. Seventeen original input features were extracted from preprocessed signals by wavelet transform, and attempts were then made to reduce these to 4 features, the linear combination of original features, by LDA. The performance of the SVM classifier with reduced features by LDA showed higher than with that by principal component analysis (PCA) and even with original features. For a cross-validation procedure, this SVM classifier was compared with Multilayer Perceptrons (MLP) and Fuzzy Inference System (FIS) classifiers. When all classifiers used the same reduced features, the overall performance of the SVM classifier was comprehensively superior to all others. Especially, the accuracy of discrimination of normal sinus rhythm (NSR), arterial premature contraction (APC), supraventricular tachycardia (SVT), premature ventricular contraction (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF) were 99.307%, 99.274%, 99.854%, 98.344%, 99.441% and 99.883%, respectively. And, even with smaller learning data, the SVM classifier offered better performance than the MLP classifier.
Files in This Item:
T200501666.pdf Download
DOI
OAK-2005-06773
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실) > 1. Journal Papers
Yonsei Authors
Yoo, Sun Kook(유선국) ORCID logo https://orcid.org/0000-0002-6032-4686
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/149913
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