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	Research on Premature Ventricular Contraction Real-time Detection Based Support Vector Machine
	Zhao Shen; Chao Hu; Ping Li; Max Q.-H Meng
	2011
会议名称	2011 International Conference on Information and Automation
会议地点	Shenzhen, China
英文摘要	This paper proposes a support vector machine (SVM) for real-time detection of premature ventricular contraction (PVC) from normal beats and others. This includes a signal feature extraction module and a statistical pattern recognition module. In feature extraction, time, frequency and morphological features are extracted, here six features are selected and made up a feature vector for input the pattern identifier. After this, an SVM is used to recognize PVC from normal beats and others; this classifier is fit for the requirements of precision and real-time at the same time. Finally, by means of testing electrocardiogram (ECG) data which from MIT-BIH arrhythmia database, the correct rating is more than 97%. Through the comparison with other methods, this achieves favorable results both in real-time and accuracy requirement.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/3392]
专题	深圳先进技术研究院_集成所
作者单位	2011
推荐引用方式 GB/T 7714	Zhao Shen,Chao Hu,Ping Li,et al. Research on Premature Ventricular Contraction Real-time Detection Based Support Vector Machine[C]. 见:2011 International Conference on Information and Automation. Shenzhen, China.

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