A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm
Joint Authors
Ding, Yongsheng
Hao, Kuangrong
Zhu, Bohui
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-18
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias.
This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias.
First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm.
Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy.
Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias.
American Psychological Association (APA)
Zhu, Bohui& Ding, Yongsheng& Hao, Kuangrong. 2013. A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-472787
Modern Language Association (MLA)
Zhu, Bohui…[et al.]. A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-472787
American Medical Association (AMA)
Zhu, Bohui& Ding, Yongsheng& Hao, Kuangrong. A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-472787
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472787