文章基本信息

标题：SPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIA
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作者：Kumar, R. Ganesh ; Kumaraswamy, Y. S.
期刊名称：Journal of Computer Science
印刷版ISSN：1549-3636
出版年度：2014
卷号：10
期号：8
页码：1582-1590
DOI：10.3844/jcssp.2014.1582.1590
出版社：Science Publications
摘要：Electro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and used as feature for arrhythmia classification. Frequency domain extracted features are classified using Radial Basis Function (RBF) and proposed Spline Activated-Feed Forward Neural Network (SA-FFNN). Experiments were conducted with the Massachusetts Institute of Technology-Boston’s Beth Israel Hospital (MIT-BIH) arrhythmia database for evaluating the proposed methods.
关键词：Multilayer Perceptron; Feed Forward Neural Network; RR Interval; Arrhythmia Classification; ECG