Corpus ID: 212496014

Recognition of sEMG for Prosthetic Control Using Static and Dynamic Neural Networks

@inproceedings{Emayavaramban2016RecognitionOS,
  title={Recognition of sEMG for Prosthetic Control Using Static and Dynamic Neural Networks},
  author={Emayavaramban},
  year={2016}
}

Emayavaramban

Published 2016

Several experiences were applied highlighting some great benefits of utilizing muscle sign in order to manage rehabilitation contraptions. This paper offers an investigating surface electromyography (sEMG) signal for classification of hand gestures to manipulate a prosthetic hand using neural networks. We assess the use of two channel surface electromyography to classify twelve person finger gestures for prosthetic control. sEMG alerts have been recorded from extensor digitorum and flexor… CONTINUE READING

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