• Title/Summary/Keyword: Artificial Netral Network

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Artificial Neural Network based Motion Classification Algorithm using Surface Electromyogram (표면 근전도를 이용한 Artificial Neural Network 기반의 동작 분류 알고리즘)

  • Jeong, E.C.;Kim, S.J.;Song, Y.R.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.6 no.1
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    • pp.67-73
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    • 2012

  • In this paper, Artificial Neural Network(ANN) based motion classification algorithm is proposed to classify wrist motions using surface electromyograms(sEMG). surface EMGs are obtained from two electrodes placed on the flexor carpi ulnaris muscle and extensor carpi ulnaris muscle of 26 subjects under no strain condition during wrist motions and used to recognize wrist motions such as up, down, left, right, and rest. Feature is extracted from obtained EMG signals in time domain for fast processing and used to classify wrist motions using ANN. DAMV, DASDV, MAV, and RMS were used as features and accuracies of motion classification based on ANN were 98.03% for DAMV, 97.97% for DASDV, 96.95% for MAV, 96.82% for RMS.

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