BIOLOGICAL SIGNAL ANALYSIS BY INDEPENDENT COMPONENT ANALYSIS USING COMPLEX WAVELET TRANSFORM-Reference-Cited by-同舟云学术

BIOLOGICAL SIGNAL ANALYSIS BY INDEPENDENT COMPONENT ANALYSIS USING COMPLEX WAVELET TRANSFORM

Published:2010-07 Issue:04 Volume:08 Page:595-608
ISSN:0219-6913
Container-title:International Journal of Wavelets, Multiresolution and Information Processing
language:en
Short-container-title:Int. J. Wavelets Multiresolut Inf. Process.

Author:

HORIHATA SATOSHI¹,ZHANG ZHONG²,IMAMURA TAKASHI²,MIYAKE TETSUO²,TODA HIROSHI³,YASUDA YOSHIFUMI⁴

Affiliation:

1. School of Dentistry at Matsudo, Nihon University, Sakaecho-nishi, 271-8587 Matsudo, Chiba, Japan

2. Department of Production System Engineering, Toyohashi University of Technology, Tempaku-cho, Toyohashi-shi, Japan

3. Media Science Research Center, Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku-cho, Toyohashi 441-8580, Japan

4. Health Science Center, Toyohashi University of Technology, Tempaku-cho, Toyohashi-shi, Japan

Abstract

Independent component analysis (ICA) is a useful method for blind source separation of two or more signals. We have previously proposed a new method combining ICA with the complex discrete wavelet transform (CDWT), in which voice and noise signals were separated using a new method. At that time, we used a simulated signal. In this study, we analyze measured biological signals by using a new method, and discuss its effectiveness. As an experiment, we try to separate an electromyogram (EMG) signal from an electrocardiogram (ECG) signal.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Information Systems,Signal Processing

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219691310003663

Reference7 articles.

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4. TRANSLATION INVARIANT RI-SPLINE WAVELET AND ITS APPLICATION ON DE-NOISING

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