Feature Extraction for the Wrist-pulse-signals in Traditional Chinese Medicine by Ensemble Empirical Mode Decomposition

被引：0

作者：

向程 ^{[1
]}

覃开蓉 ^{[2
]}

机构：

[1] Department of Electrical and Computer Engineering,National University of Singapore,Singapore

[2] Department of Electrical and Computer Engineering,National University of Singapore,Singapore Shanghai Research Center of Acupuncture & Meridian,Shanghai 201203,P.R.China

来源：

Journal of Acupuncture and Tuina Science | 2008年 / 6卷 / 06期

关键词：

EEMD;

D O I：

暂无

中图分类号：

R241.1 [脉学];

学科分类号：

100505 ;

摘要：

Pulse diagnosis plays a vital role in Traditional Chinese Medicine(TCM).To extract effective and properfeatures from the wrist-pulse-signals is a crucial step for the recognition and classification of the pulsesignals.Although the analysis in the time domain is also very effective for a lot of pulse types(SHU et al.,2007),the frequency and time-frequency analysis are usually used in the literature(YAN et al.,2005;YUEet al.,2006)because the pulse signals are non-stationary and non-periodic time series in the pathologicalstates.In recent years,a new time-frequency analysis method,Hilbert-HUANG Transform proposed by

引用

页码：327 / 327

页数：1

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