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A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study
Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users’ intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779154/ https://www.ncbi.nlm.nih.gov/pubmed/35062627 http://dx.doi.org/10.3390/s22020666 |
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author | Alizadeh-Meghrazi, Milad Sidhu, Gurjant Jain, Saransh Stone, Michael Eskandarian, Ladan Toossi, Amirali Popovic, Milos R. |
author_facet | Alizadeh-Meghrazi, Milad Sidhu, Gurjant Jain, Saransh Stone, Michael Eskandarian, Ladan Toossi, Amirali Popovic, Milos R. |
author_sort | Alizadeh-Meghrazi, Milad |
collection | PubMed |
description | Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users’ intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand. |
format | Online Article Text |
id | pubmed-8779154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87791542022-01-22 A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study Alizadeh-Meghrazi, Milad Sidhu, Gurjant Jain, Saransh Stone, Michael Eskandarian, Ladan Toossi, Amirali Popovic, Milos R. Sensors (Basel) Article Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users’ intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand. MDPI 2022-01-15 /pmc/articles/PMC8779154/ /pubmed/35062627 http://dx.doi.org/10.3390/s22020666 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 Alizadeh-Meghrazi, Milad Sidhu, Gurjant Jain, Saransh Stone, Michael Eskandarian, Ladan Toossi, Amirali Popovic, Milos R. A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title | A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title_full | A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title_fullStr | A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title_full_unstemmed | A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title_short | A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study |
title_sort | mass-producible washable smart garment with embedded textile emg electrodes for control of myoelectric prostheses: a pilot study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779154/ https://www.ncbi.nlm.nih.gov/pubmed/35062627 http://dx.doi.org/10.3390/s22020666 |
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