Classification of Myoelectric Surface Signals of Hand Movements using Supervised Learning Techniques

Marisol Flores, Juan Medina, Cristian Álamo

Abstract

This work presents a comparative study of techniques to classify four hand movements (flexion, extension, opening and closure) using myoelectric signals measured at the forearm in two separate channels: the brachioradialis and the flexor carpi ulnaris (FCU) muscle. The process of signal acquisition is described, as well as signal normalization, hybrid feature extraction and classification using two supervised learning techniques; i.e., backpropagation and support vector machines. The classifiers were trained using the raw data from the input signal. It was verified that the accuracy of the classification is improved by feature extraction up to 2.25%, yielding a successful average classification rate of 91.00%.

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Paper Citation


in Harvard Style

Flores M., Medina J. and Álamo C. (2021). Classification of Myoelectric Surface Signals of Hand Movements using Supervised Learning Techniques.In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, ISBN 978-989-758-490-9, pages 243-251. DOI: 10.5220/0010281802430251


in Bibtex Style

@conference{biosignals21,
author={Marisol Flores and Juan Medina and Cristian Álamo},
title={Classification of Myoelectric Surface Signals of Hand Movements using Supervised Learning Techniques},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,},
year={2021},
pages={243-251},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010281802430251},
isbn={978-989-758-490-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,
TI - Classification of Myoelectric Surface Signals of Hand Movements using Supervised Learning Techniques
SN - 978-989-758-490-9
AU - Flores M.
AU - Medina J.
AU - Álamo C.
PY - 2021
SP - 243
EP - 251
DO - 10.5220/0010281802430251