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

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

R.T Lauer, C.A Laughton, M Orlin and B.T Smith
2003 IEEE 29th Annual Proceedings of Bioengineering Conference, v 2003-, pp 142-143
2003

Abstract

Band pass filters Bandwidth Chebyshev approximation Discrete wavelet transforms Electromyography Filtering Leg Muscles Neuromuscular Root mean square
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.

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Web of Science research areas
Computer Science, Artificial Intelligence
Engineering, Biomedical
Instruments & Instrumentation
Radiology, Nuclear Medicine & Medical Imaging
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