Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal

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摘要

ObjectiveThis paper presents an effective cardiac arrhythmia classification algorithm using the heart rate variability (HRV) signal. The proposed algorithm is based on the generalized discriminant analysis (GDA) feature reduction scheme and the support vector machine (SVM) classifier.

论文关键词：Arrhythmia classification,Generalized discriminant analysis,Heart rate variability,Nonlinear analysis,Support vector machine

论文评审过程：Received 14 July 2007, Revised 24 April 2008, Accepted 28 April 2008, Available online 27 June 2008.

论文官网地址：https://doi.org/10.1016/j.artmed.2008.04.007