Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss
This study presents a model-based sensitivity analysis of the strength of voluntary muscle contraction with respect to different patterns of motor unit loss. A motor unit pool model was implemented including simulation of a motor neuron pool, muscle force, and surface electromyogram (EMG) signals. T...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2021/5513224 |
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| _version_ | 1841524881683906560 |
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| author | Chengjun Huang Maoqi Chen Yingchun Zhang Sheng Li Ping Zhou |
| author_facet | Chengjun Huang Maoqi Chen Yingchun Zhang Sheng Li Ping Zhou |
| author_sort | Chengjun Huang |
| collection | DOAJ |
| description | This study presents a model-based sensitivity analysis of the strength of voluntary muscle contraction with respect to different patterns of motor unit loss. A motor unit pool model was implemented including simulation of a motor neuron pool, muscle force, and surface electromyogram (EMG) signals. Three different patterns of motor unit loss were simulated, including (1) motor unit loss restricted to the largest ones, (2) motor unit loss restricted to the smallest ones, and (3) motor unit loss without size restriction. The model outputs including muscle force amplitude, variability, and the resultant EMG-force relation were quantified under two different motor neuron firing strategies. It was found that motor unit loss restricted to the largest ones had the most dominant impact on muscle strength and significantly changed the EMG-force relation, while loss restricted to the smallest motor units had a pronounced effect on force variability. These findings provide valuable insight toward our understanding of the neurophysiological mechanisms underlying experimental observations of muscle strength, force control, and EMG-force relation in both normal and pathological conditions. |
| format | Article |
| id | doaj-art-9f92414a5c0c4406a0602e38d7111b33 |
| institution | Kabale University |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-9f92414a5c0c4406a0602e38d7111b332025-02-03T05:47:09ZengWileyNeural Plasticity2090-59041687-54432021-01-01202110.1155/2021/55132245513224Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit LossChengjun Huang0Maoqi Chen1Yingchun Zhang2Sheng Li3Ping Zhou4Guangdong Work Injury Rehabilitation Center, Guangzhou, ChinaInstitute of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao, ChinaDepartment of Biomedical Engineering, University of Houston, Houston, TX, USADepartment of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, TX, USAInstitute of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao, ChinaThis study presents a model-based sensitivity analysis of the strength of voluntary muscle contraction with respect to different patterns of motor unit loss. A motor unit pool model was implemented including simulation of a motor neuron pool, muscle force, and surface electromyogram (EMG) signals. Three different patterns of motor unit loss were simulated, including (1) motor unit loss restricted to the largest ones, (2) motor unit loss restricted to the smallest ones, and (3) motor unit loss without size restriction. The model outputs including muscle force amplitude, variability, and the resultant EMG-force relation were quantified under two different motor neuron firing strategies. It was found that motor unit loss restricted to the largest ones had the most dominant impact on muscle strength and significantly changed the EMG-force relation, while loss restricted to the smallest motor units had a pronounced effect on force variability. These findings provide valuable insight toward our understanding of the neurophysiological mechanisms underlying experimental observations of muscle strength, force control, and EMG-force relation in both normal and pathological conditions.http://dx.doi.org/10.1155/2021/5513224 |
| spellingShingle | Chengjun Huang Maoqi Chen Yingchun Zhang Sheng Li Ping Zhou Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss Neural Plasticity |
| title | Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss |
| title_full | Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss |
| title_fullStr | Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss |
| title_full_unstemmed | Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss |
| title_short | Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss |
| title_sort | model based analysis of muscle strength and emg force relation with respect to different patterns of motor unit loss |
| url | http://dx.doi.org/10.1155/2021/5513224 |
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