Improved complete ensemble EMD: A suitable tool for biomedical signal processing

被引：1021

作者：

Colominas, Marcelo A. ^{[1
,2
]}

Schlotthauer, Gaston ^{[1
,2
]}

Torres, Maria E. ^{[1
,2
]}

机构：

[1] Univ Nacl Entre Rios, Lab Senales & Dinam Lineales, Oro Verde, Entre Rios, Argentina

[2] Consejo Nacl Invest Cient & Tecn, Buenos Aires, DF, Argentina

来源：

BIOMEDICAL SIGNAL PROCESSING AND CONTROL | 2014年 / 14卷

关键词：

Empirical mode decomposition (EMD); Noise-assisted data analysis; Electroglottography; Ventricular fibrillation; Epileptic seizure; EMPIRICAL MODE DECOMPOSITION; AUTOMATIC DETECTION;

D O I：

10.1016/j.bspc.2014.06.009

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The empirical mode decomposition (EMD) decomposes non-stationary signals that may stem from non-linear systems, in a local and fully data-driven manner. Noise-assisted versions have been proposed to alleviate the so-called "mode mixing" phenomenon, which may appear when real signals are analyzed. Among them, the complete ensemble EMD with adaptive noise (CEEMDAN) recovered the completeness property of EMD. In this work we present improvements on this last technique, obtaining components with less noise and more physical meaning. Artificial signals are analyzed to illustrate the capabilities of the new method. Finally, several real biomedical signals are decomposed, obtaining components that represent physiological phenomenons. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：19 / 29

页数：11

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