期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：2
页码：211-222
DOI：10.14257/ijsip.2014.7.2.20
出版社：SERSC
摘要：The aim of this paper is twofold. First, we define an ECG feature parameter set (32 features) which could represent ECG signal as adequately as possible for diagnosing requirements. Second, we design an automatic classification framework. After benchmark point detection, feature parameter will be extracted. And then the classifier methods and its comparison based on SVM and QNN are presented. The long-term objective is to design a thorough system to realize the recognition of real-time ECG signal and enhance medical treatment
关键词：ECG classification; RQS wave detection; Wavelet Transform; Principal ; component analysis; Rough sets; Support vector machine; Quantum Neural Network
