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The influence of spatial distribution of motor unit density and level of motor unit recruitment on the estimation of muscle fiber conduction velocity: A simulation study.

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Τίτλος: The influence of spatial distribution of motor unit density and level of motor unit recruitment on the estimation of muscle fiber conduction velocity: A simulation study.
Συγγραφείς: Tang P; Qingdao University, Qingdao 266071, China. Electronic address: tangpeng@qdu.edu.cn., Shin H; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: henryhongsukshin@uhrs.edu.cn., Zhang C; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: zhangchuan@uhrs.edu.cn., Chi J; Qingdao University, Qingdao 266071, China. Electronic address: chijieru@qdu.edu.cn., Huang C; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: huangchengjun@uhrs.edu.cn., Zhou P; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China; Department of Rehabilitation Medicine, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, 266113, China; Shandong Key Laboratory of Neurorehabilitation, University of Health and Rehabilitation Sciences, Qingdao 266113, China. Electronic address: dr.ping.zhou@outlook.com.
Πηγή: Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology [J Electromyogr Kinesiol] 2026 Oct; Vol. 90, pp. 103192. Date of Electronic Publication: 2026 Jul 31.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: England NLM ID: 9109125 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-5711 (Electronic) Linking ISSN: 10506411 NLM ISO Abbreviation: J Electromyogr Kinesiol Subsets: MEDLINE
Imprint Name(s): Publication: <1995- >: Oxford : Elsevier
Original Publication: New York, N.Y. : Raven Press, 1991-
Ιατρικοί όροι (MeSH): Recruitment, Neurophysiological*/physiology , Muscle Fibers, Skeletal*/physiology , Neural Conduction*/physiology , Motor Neurons*/physiology , Action Potentials*/physiology , Muscle, Skeletal*/physiology , Muscle Contraction*/physiology , Models, Neurological*, Electromyography/methods ; Humans ; Computer Simulation
Περίληψη: Background: This study aims to investigate how alterations in the spatial distribution of motor unit (MU) density, such as those resulting from neuromuscular disorders, affect the accuracy of muscle fiber conduction velocity (MFCV) estimation, and to examine whether different levels of MU recruitment can mitigate these effects.
Methods: We used the Fuglevand model to simulate three different MU densities across the muscle: edge-clustered, center-clustered, and a uniform distribution. MFCV was estimated from simulated double differential surface electromyography (sEMG) signals at four MU recruitment levels using a cross-correlation method.
Results: MU density spatial distribution influenced MFCV estimation accuracy. The highest estimation accuracy was achieved in regions of high MU density and lowest in regions of low MU density. Level of MU recruitment influenced MFCV estimation accuracy, with higher recruitment partially compensating for estimation errors. A lower number of MUs reduced overall estimation accuracy.
Conclusions: The spatial distribution of MU density is an important factor in MFCV estimation. This study provides quantitative benchmarks for how spatial variations in MU density affect MFCV estimation accuracy. The finding highlights the importance of MU density, recruitment level, and total number of MUs in estimating MFCV, all of which may be altered in patients with neuromuscular disorders.
(Copyright © 2026. Published by Elsevier Ltd.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: High-density surface electromyography; Motor unit density distribution; Muscle Fiber conduction velocity
Entry Date(s): Date Created: 20260805 Date Completed: 20260923 Latest Revision: 20260923
Update Code: 20260924
DOI: 10.1016/j.jelekin.2026.103192
PMID: 42556082
Βάση Δεδομένων: MEDLINE
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  Label: Title
  Group: Ti
  Data: The influence of spatial distribution of motor unit density and level of motor unit recruitment on the estimation of muscle fiber conduction velocity: A simulation study.
– Name: Author
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  Group: Au
  Data: &lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Tang+P%22&quot;&gt;Tang P&lt;/searchLink&gt;; Qingdao University, Qingdao 266071, China. Electronic address: tangpeng@qdu.edu.cn.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Shin+H%22&quot;&gt;Shin H&lt;/searchLink&gt;; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: henryhongsukshin@uhrs.edu.cn.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Zhang+C%22&quot;&gt;Zhang C&lt;/searchLink&gt;; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: zhangchuan@uhrs.edu.cn.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Chi+J%22&quot;&gt;Chi J&lt;/searchLink&gt;; Qingdao University, Qingdao 266071, China. Electronic address: chijieru@qdu.edu.cn.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Huang+C%22&quot;&gt;Huang C&lt;/searchLink&gt;; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China. Electronic address: huangchengjun@uhrs.edu.cn.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Zhou+P%22&quot;&gt;Zhou P&lt;/searchLink&gt;; School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266113, China; Department of Rehabilitation Medicine, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, 266113, China; Shandong Key Laboratory of Neurorehabilitation, University of Health and Rehabilitation Sciences, Qingdao 266113, China. Electronic address: dr.ping.zhou@outlook.com.
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  Data: &lt;i&gt;Publisher: &lt;/i&gt;&lt;searchLink fieldCode=&quot;PB&quot; term=&quot;%22Elsevier%22&quot;&gt;Elsevier &lt;/searchLink&gt;&lt;i&gt;Country of Publication: &lt;/i&gt;England &lt;i&gt;NLM ID: &lt;/i&gt;9109125 &lt;i&gt;Publication Model: &lt;/i&gt;Print-Electronic &lt;i&gt;Cited Medium: &lt;/i&gt;Internet &lt;i&gt;ISSN: &lt;/i&gt;1873-5711 (Electronic) &lt;i&gt;Linking ISSN: &lt;/i&gt;&lt;searchLink fieldCode=&quot;IS&quot; term=&quot;%2210506411%22&quot;&gt;10506411 &lt;/searchLink&gt;&lt;i&gt;NLM ISO Abbreviation: &lt;/i&gt;J Electromyogr Kinesiol &lt;i&gt;Subsets: &lt;/i&gt;MEDLINE
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  Data: &lt;i&gt;Publication&lt;/i&gt;: &lt;1995- &gt;: Oxford : Elsevier&lt;br /&gt;&lt;i&gt;Original Publication&lt;/i&gt;: New York, N.Y. : Raven Press, 1991-
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– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: This study aims to investigate how alterations in the spatial distribution of motor unit (MU) density, such as those resulting from neuromuscular disorders, affect the accuracy of muscle fiber conduction velocity (MFCV) estimation, and to examine whether different levels of MU recruitment can mitigate these effects.&lt;br /&gt;Methods: We used the Fuglevand model to simulate three different MU densities across the muscle: edge-clustered, center-clustered, and a uniform distribution. MFCV was estimated from simulated double differential surface electromyography (sEMG) signals at four MU recruitment levels using a cross-correlation method.&lt;br /&gt;Results: MU density spatial distribution influenced MFCV estimation accuracy. The highest estimation accuracy was achieved in regions of high MU density and lowest in regions of low MU density. Level of MU recruitment influenced MFCV estimation accuracy, with higher recruitment partially compensating for estimation errors. A lower number of MUs reduced overall estimation accuracy.&lt;br /&gt;Conclusions: The spatial distribution of MU density is an important factor in MFCV estimation. This study provides quantitative benchmarks for how spatial variations in MU density affect MFCV estimation accuracy. The finding highlights the importance of MU density, recruitment level, and total number of MUs in estimating MFCV, all of which may be altered in patients with neuromuscular disorders.&lt;br /&gt; (Copyright &#169; 2026. Published by Elsevier Ltd.)
– Name: Abstract
  Label: Competing Interests
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  Data: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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  Data: &lt;i&gt;Keywords: &lt;/i&gt;High-density surface electromyography; Motor unit density distribution; Muscle Fiber conduction velocity
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  Data: &lt;i&gt;Date Created: &lt;/i&gt;20260805 &lt;i&gt;Date Completed: &lt;/i&gt;20260923 &lt;i&gt;Latest Revision: &lt;/i&gt;20260923
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  Data: 10.1016/j.jelekin.2026.103192
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        Value: 10.1016/j.jelekin.2026.103192
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 103192
    Subjects:
      – SubjectFull: Electromyography methods
        Type: general
      – SubjectFull: Humans
        Type: general
      – SubjectFull: Computer Simulation
        Type: general
      – SubjectFull: Recruitment, Neurophysiological physiology
        Type: general
      – SubjectFull: Muscle Fibers, Skeletal physiology
        Type: general
      – SubjectFull: Neural Conduction physiology
        Type: general
      – SubjectFull: Motor Neurons physiology
        Type: general
      – SubjectFull: Action Potentials physiology
        Type: general
      – SubjectFull: Muscle, Skeletal physiology
        Type: general
      – SubjectFull: Muscle Contraction physiology
        Type: general
      – SubjectFull: Models, Neurological
        Type: general
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      – TitleFull: The influence of spatial distribution of motor unit density and level of motor unit recruitment on the estimation of muscle fiber conduction velocity: A simulation study.
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              Text: 2026 Oct
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