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Estimation of Time-Frequency Muscle Synergy in Wrist Movements

Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship...

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Autores principales: Xie, Ping, Chang, Qingya, Zhang, Yuanyuan, Dong, Xiaojiao, Yu, Jinxu, Chen, Xiaoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140749/
https://www.ncbi.nlm.nih.gov/pubmed/35626589
http://dx.doi.org/10.3390/e24050707
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author Xie, Ping
Chang, Qingya
Zhang, Yuanyuan
Dong, Xiaojiao
Yu, Jinxu
Chen, Xiaoling
author_facet Xie, Ping
Chang, Qingya
Zhang, Yuanyuan
Dong, Xiaojiao
Yu, Jinxu
Chen, Xiaoling
author_sort Xie, Ping
collection PubMed
description Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0–125 Hz during the MC stage is more than that in the frequency band of 125–250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625–156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125–156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system.
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spelling pubmed-91407492022-05-28 Estimation of Time-Frequency Muscle Synergy in Wrist Movements Xie, Ping Chang, Qingya Zhang, Yuanyuan Dong, Xiaojiao Yu, Jinxu Chen, Xiaoling Entropy (Basel) Article Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0–125 Hz during the MC stage is more than that in the frequency band of 125–250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625–156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125–156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system. MDPI 2022-05-16 /pmc/articles/PMC9140749/ /pubmed/35626589 http://dx.doi.org/10.3390/e24050707 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
Xie, Ping
Chang, Qingya
Zhang, Yuanyuan
Dong, Xiaojiao
Yu, Jinxu
Chen, Xiaoling
Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title_full Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title_fullStr Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title_full_unstemmed Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title_short Estimation of Time-Frequency Muscle Synergy in Wrist Movements
title_sort estimation of time-frequency muscle synergy in wrist movements
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140749/
https://www.ncbi.nlm.nih.gov/pubmed/35626589
http://dx.doi.org/10.3390/e24050707
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