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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...

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Detalles Bibliográficos
Autores principales: Mechtenberg, Malte, Schneider, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
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).
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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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