Wavelet transform theory and its application in EMG signal processing

Author

Zhang, Xu ; Wang, Yu ; Han, Ray P S

Author_Institution

Qingdao Univ., Qingdao, China

Volume

5

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

2234

Lastpage

2238

Abstract

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.

Keywords

electromyography; feature extraction; medical signal processing; muscle; patient rehabilitation; time-frequency analysis; wavelet transforms; EMG signal processing; clinical diagnosis; electromyogram signal; feature extraction; muscle activity; rehabilitation medicine; signal denoising; sport medicine; time-frequency analysis; wavelet transform theory; Electromyography; Feature extraction; Multiresolution analysis; Noise reduction; Wavelet transforms; EMG signal processing; feature extraction; multi-resolution analysis; wavelet de-noising; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5931-5

Type

conf

DOI

10.1109/FSKD.2010.5569532

Filename

5569532