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	Multilayer self-organizing maps method for cluster electrocardiogram QRS wave clustering
	Yang Rongfeng ; Wei Yixiang
	2010-05-06 ; 2010-05-06
关键词	Practical Theoretical or Mathematical/ electrocardiography iterative methods medical signal processing self-organising feature maps/ multilayer self-organizing maps electrocardiogram QRS wave clustering adaptive parameter learning iteration MIT-BIH data premature ventricular contraction/ A8730C Electrical activity in neurophysiological processes A0260 Numerical approximation and analysis B7510D Bioelectric signals B6140 Signal processing and detection B0290F Interpolation and function approximation (numerical analysis) C7330 Biology and medical computing C5290 Neural computing techniques C4130 Interpolation and function approximation (numerical analysis)
中文摘要	This paper describes the applications of multilayer self-organizing maps to cluster electrocardiogram QRS waves. Two normalized lead electrocardiogram data were fit to the first layer self-organizing map, with the outputs used as the input to the second layer to achieve clustering results. An intertive adaptive parameter learning iteration process enhanced the self-organizing maps net performance. The clustering capability was evaluated with MIT-BIH data. The results indicate the efficient clustering ability with a 99.1% true positive rate in detecting premature ventricular contraction (PVC) class abnormal electrocardiogram beats, which is better than the ART-2 net and match method.
语种	中文 ; 中文
出版者	Tsinghua Univ. Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/10850]
专题	清华大学
推荐引用方式 GB/T 7714	Yang Rongfeng,Wei Yixiang. Multilayer self-organizing maps method for cluster electrocardiogram QRS wave clustering[J],2010, 2010.
APA	Yang Rongfeng,&Wei Yixiang.(2010).Multilayer self-organizing maps method for cluster electrocardiogram QRS wave clustering..
MLA	Yang Rongfeng,et al."Multilayer self-organizing maps method for cluster electrocardiogram QRS wave clustering".(2010).

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