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Classification of Surface Electromyogram Signals Acquired from the Forearm of a Healthy Volunteer

Uvanesh, K and Thakur, Goutam and Nayak, Suraj Kumar and Mohapatra, Biswajit and Champaty, Biswajeet and Tibarewala, D. N. and Pal, Kunal (2016) Classification of Surface Electromyogram Signals Acquired from the Forearm of a Healthy Volunteer. In: Classification and Clustering in Biomedical Signal Processing. IGI Global, pp. 315-317.

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Abstract

Surface EMG (sEMG) signals from the palmaris longus, flexor carpi radialis and flexor carpi ulnaris muscles were recorded using an in-house developed EMG signal acquisition system. The bandwidth of the acquisition system was 1500 Hz. The extracted sEMG signal was processed using Discrete Wavelet Transform (DWT). The features of the extracted and the wavelet processed signals were determined and were used for probable classification using Artificial Neural Network (ANN). A classification efficiency of more than 90% was achieved using ANN classifiers. The results suggested that the sEMG may be successfully used for designing efficient control system

Item Type: Book Section
Uncontrolled Keywords: EMG, ANN, DWT
Subjects: Engineering > MIT Manipal > Biomedical
Depositing User: MIT Library
Date Deposited: 14 Jan 2017 10:30
Last Modified: 14 Jan 2017 10:30
URI: http://eprints.manipal.edu/id/eprint/148118

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