TY - GEN
T1 - Classification of myoelectric surface signals of hand movements using supervised learning techniques
AU - Galarza Flores, Marisol Cristel
AU - López del Álamo, Cristian
AU - Miranda Medina, Juan Felipe
N1 - Publisher Copyright:
Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
PY - 2021
Y1 - 2021
N2 - 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%.
AB - 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%.
KW - Electromyography
KW - Neural Networks
KW - Principal Component Analysis
KW - Support Vector Machines
KW - Wavelets
UR - http://www.scopus.com/inward/record.url?scp=85103830544&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85103830544
T3 - BIOSIGNALS 2021 - 14th International Conference on Bio-Inspired Systems and Signal Processing; Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021
SP - 243
EP - 251
BT - BIOSIGNALS 2021 - 14th International Conference on Bio-Inspired Systems and Signal Processing; Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021
A2 - Bracken, Bethany
A2 - Fred, Ana
A2 - Gamboa, Hugo
PB - SciTePress
T2 - 14th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2021 - Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021
Y2 - 11 February 2021 through 13 February 2021
ER -