Wavelet transform theory and its application in EMG signal processing

Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. The electromyogram (EMG) signals arising from muscle activities have become a useful tool for clinical diagnosis, rehabilitation medicine and sport medicine. In this paper, a ti...

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Bibliographic Details
Published in2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery Vol. 5; pp. 2234 - 2238
Main Authors Xu Zhang, Yu Wang, Han, R P S
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.08.2010
Subjects
Electromyography
EMG signal processing
Feature extraction
multi-resolution analysis
Multiresolution analysis
Noise reduction
wavelet de-noising
wavelet transform
Wavelet transforms
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ISBN1424459311
9781424459315
DOI10.1109/FSKD.2010.5569532

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Summary:Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. The electromyogram (EMG) signals arising from muscle activities have become a useful tool for clinical diagnosis, rehabilitation medicine and sport medicine. In this paper, a time-frequency analysis based on the wavelet transform of the EMG signals is presented with a focus on 2 areas: de-noising and feature extraction.
ISBN:1424459311
9781424459315
DOI:10.1109/FSKD.2010.5569532