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Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements

Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This st...

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Autores principales: Gomez-Correa, Manuela, Cruz-Ortiz, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416605/
https://www.ncbi.nlm.nih.gov/pubmed/36015692
http://dx.doi.org/10.3390/s22165931
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author Gomez-Correa, Manuela
Cruz-Ortiz, David
author_facet Gomez-Correa, Manuela
Cruz-Ortiz, David
author_sort Gomez-Correa, Manuela
collection PubMed
description Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section’s diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals.
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spelling pubmed-94166052022-08-27 Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements Gomez-Correa, Manuela Cruz-Ortiz, David Sensors (Basel) Article Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section’s diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals. MDPI 2022-08-09 /pmc/articles/PMC9416605/ /pubmed/36015692 http://dx.doi.org/10.3390/s22165931 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gomez-Correa, Manuela
Cruz-Ortiz, David
Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title_full Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title_fullStr Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title_full_unstemmed Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title_short Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
title_sort low-cost wearable band sensors of surface electromyography for detecting hand movements
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416605/
https://www.ncbi.nlm.nih.gov/pubmed/36015692
http://dx.doi.org/10.3390/s22165931
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