Use of RBF neural network in EMG signal noise removal

Authors:
V. R. Mankar;A. A. Ghatol
Affiliations:
Head of Electronics Department, Government Polytechnic, Amravati, MS, India;Dr. B.A. Technological University, Raigarh, MS, India
Venue:
WSEAS Transactions on Circuits and Systems
Year:
2008

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Abstract

The bioelectric potentials associated with muscle activity constitute the electromyogram (EMG). EMG signal is used in biomedical applications to detect abnormal muscle electrical activity that occur in many diseases and conditions like muscular dystrophy, inflammation of muscles, pinched nerves, peripheral nerve damages, amyotrophic lateral sclerosis, disc herniation, myasthenia gravis and others. In this paper, it is depicted that an RBF neural network as compared with other types of neural networks can be effectively used for EMG signal noise removal, which is a typical nonlinear multivariable regression problem. The performance parameters i.e. MSE and correlation coefficient are found to be in the expected range of values.