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A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model
Motion predictions for limbs can be performed using commonly called Hill-based muscle models. For this type of models, a surface electromyogram (sEMG) of the muscle serves as an input signal for the activation of the muscle model. However, the Hill model needs additional information about the mechan...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359103/ https://www.ncbi.nlm.nih.gov/pubmed/37483540 http://dx.doi.org/10.3389/fnbot.2023.1179224 |
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author | Mechtenberg, Malte Schneider, Axel |
author_facet | Mechtenberg, Malte Schneider, Axel |
author_sort | Mechtenberg, Malte |
collection | PubMed |
description | Motion predictions for limbs can be performed using commonly called Hill-based muscle models. For this type of models, a surface electromyogram (sEMG) of the muscle serves as an input signal for the activation of the muscle model. However, the Hill model needs additional information about the mechanical system state of the muscle (current length, velocity, etc.) for a reliable prediction of the muscle force generation and, hence, the prediction of the joint motion. One feature that contains potential information about the state of the muscle is the position of the center of the innervation zone. This feature can be further extracted from the sEMG. To find the center, a wavelet-based algorithm is proposed that localizes motor unit potentials in the individual channels of a single-column sEMG array and then identifies innervation point candidates. In the final step, these innervation point candidates are clustered in a density-based manner. The center of the largest cluster is the estimated center of the innervation zone. The algorithm has been tested in a simulation. For this purpose, an sEMG simulator was developed and implemented that can compute large motor units (1,000's of muscle fibers) quickly (within seconds on a standard PC). |
format | Online Article Text |
id | pubmed-10359103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103591032023-07-21 A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model Mechtenberg, Malte Schneider, Axel Front Neurorobot Neuroscience Motion predictions for limbs can be performed using commonly called Hill-based muscle models. For this type of models, a surface electromyogram (sEMG) of the muscle serves as an input signal for the activation of the muscle model. However, the Hill model needs additional information about the mechanical system state of the muscle (current length, velocity, etc.) for a reliable prediction of the muscle force generation and, hence, the prediction of the joint motion. One feature that contains potential information about the state of the muscle is the position of the center of the innervation zone. This feature can be further extracted from the sEMG. To find the center, a wavelet-based algorithm is proposed that localizes motor unit potentials in the individual channels of a single-column sEMG array and then identifies innervation point candidates. In the final step, these innervation point candidates are clustered in a density-based manner. The center of the largest cluster is the estimated center of the innervation zone. The algorithm has been tested in a simulation. For this purpose, an sEMG simulator was developed and implemented that can compute large motor units (1,000's of muscle fibers) quickly (within seconds on a standard PC). Frontiers Media S.A. 2023-07-06 /pmc/articles/PMC10359103/ /pubmed/37483540 http://dx.doi.org/10.3389/fnbot.2023.1179224 Text en Copyright © 2023 Mechtenberg and Schneider. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Mechtenberg, Malte Schneider, Axel A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title | A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title_full | A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title_fullStr | A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title_full_unstemmed | A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title_short | A method for the estimation of a motor unit innervation zone center position evaluated with a computational sEMG model |
title_sort | method for the estimation of a motor unit innervation zone center position evaluated with a computational semg model |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359103/ https://www.ncbi.nlm.nih.gov/pubmed/37483540 http://dx.doi.org/10.3389/fnbot.2023.1179224 |
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