title: Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.
abstract: Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.
authors: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China. lihongqiang@tjpu.edu.cn.
authors: Hongqiang
authors: H
authors: Li
authors: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China. 1431096018@stu.tjpu.edu.cn.
authors: Danyang
authors: D
authors: Yuan
authors: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China. wangyouxi@tjpu.edu.cn.
authors: Youxi
authors: Y
authors: Wang
authors: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China. 1430092037@stu.tjpu.edu.cn.
authors: Dianyin
authors: D
authors: Cui
authors: Tianjin Chest Hospital, Tianjin 300222, China. caolutj@yahoo.com.cn.
authors: Lu
authors: L
authors: Cao
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000150:complications / Q000175:diagnosis*; D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods*; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine; D058067:Wavelet Analysis
keywords: ECG recognition system; kernel-independent component analysis; multi-domain features; support vector machine