Wavelet decomposition for the identification of EMG activity in the gait cycle

Author

Lauer, R.T. ; Laughton, C.A. ; Orlin, M. ; Smith, B.T.

Author_Institution

Shriners Hospitals for Children, Philadelphia, PA, USA

fYear

2003

Firstpage

142

Lastpage

143

Abstract

Accurate determination of the onset and offset of muscle activity in relation to the gait cycle is essential for understanding the pathology of certain neuromuscular disorders and for evaluating the effectiveness of treatment. This study examined the use of the discrete wavelet transform as an automated method for the detection of EMG activity. Comparisons of the wavelet method to a root mean squared algorithm and visual observation indicate that the wavelet method could be ideal for the detection of EMG activity during gait, but further studies are required.

Keywords

discrete wavelet transforms; electromyography; gait analysis; medical signal processing; EMG activity identification; automated method; discrete wavelet transform; gait cycle; muscle activity offset; muscle activity onset; neuromuscular disorders; pathology; root mean squared algorithm; treatment effectiveness; visual observation; wavelet decomposition; Band pass filters; Bandwidth; Chebyshev approximation; Discrete wavelet transforms; Electromyography; Filtering; Leg; Muscles; Neuromuscular; Root mean square;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 2003 IEEE 29th Annual, Proceedings of

Print_ISBN

0-7803-7767-2

Type

conf

DOI

10.1109/NEBC.2003.1216032

Filename

1216032