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Authors: Paulo L. Viana 1 ; Victoria S. Fujii 1 ; Larissa M. Lima 1 ; Gabriel L. Ouriques 1 ; Gustavo C. Oliveira 2 ; Renato Varoto 3 and Alberto Cliquet Jr. 1 ; 2 ; 3

Affiliations: 1 Department of Electrical and Computer Engineering, Trabalhador São-Carlense Avenue, 400, São Carlos, Brazil ; 2 University of São Paulo Interunits Graduate Program in Bioengineering, University of São Paulo, Trabalhador São-Carlense Avenue, 400, São Carlos, Brazil ; 3 Department of Orthopedics and Traumatology, University of Campinas, Cidade Universitária Zeferino Vaz, Campinas, Brazil

Keyword(s): Neural Networks, Hand Movement, Electromyography, Rehabilitation, Machine Learning.

Abstract: In this paper we present the development of an artificial neural network that uses surface EMG data from two forearm muscles to classify hand movements and gestures. We trained our network to classify three different sets of movements, using EMG data from six healthy subjects. We were able to achieve hit rates of above 99% in the training sets and hit rates of above 85% in all three test sets, with a maximum of 88.8% for the second movement set. Advantages of the proposed method include small number of electrodes, reduced complexity, computational cost and response time.

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Paper citation in several formats:
Viana, P.; Fujii, V.; Lima, L.; Ouriques, G.; Oliveira, G.; Varoto, R. and Cliquet Jr., A. (2019). An Artificial Neural Network for Hand Movement Classification using Surface Electromyography. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS; ISBN 978-989-758-353-7; ISSN 2184-4305, SciTePress, pages 185-192. DOI: 10.5220/0007404201850192

@conference{biosignals19,
author={Paulo L. Viana. and Victoria S. Fujii. and Larissa M. Lima. and Gabriel L. Ouriques. and Gustavo C. Oliveira. and Renato Varoto. and Alberto {Cliquet Jr.}.},
title={An Artificial Neural Network for Hand Movement Classification using Surface Electromyography},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS},
year={2019},
pages={185-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007404201850192},
isbn={978-989-758-353-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS
TI - An Artificial Neural Network for Hand Movement Classification using Surface Electromyography
SN - 978-989-758-353-7
IS - 2184-4305
AU - Viana, P.
AU - Fujii, V.
AU - Lima, L.
AU - Ouriques, G.
AU - Oliveira, G.
AU - Varoto, R.
AU - Cliquet Jr., A.
PY - 2019
SP - 185
EP - 192
DO - 10.5220/0007404201850192
PB - SciTePress

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