Evidence map›Paper›PMID 23227110›Full record

ArticleComputational and mathematical methods in medicine2012

Spreading out muscle mass within a Hill-type model: a computer simulation study.

Michael Günther, Oliver Röhrle, Daniel F B Haeufle, Syn Schmitt

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Effects of muscle mass on muscle force predictions in human movement.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. [Musculoskeletal biomechanical analysis of the three-dimensional gastrocnemius and soleus muscles].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    Article
  4. Article
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  6. A theory of physiological similarity in muscle-driven motion.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Numerical instability of Hill-type muscle models.Journal of the Royal Society, Interface · 2023
    Review
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  9. Article
  10. Antimicrobial Resistance and Virulence Factor ofInfection and drug resistance · 2021
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Michael GüntherInstitut für Sport-und Bewegungswissenschaft, Universität Stuttgart, Allmandring 28, 70569 Stuttgart, Germany. s7gumi@uni-jena.de
Oliver Röhrle
Daniel F B Haeufle
Syn Schmitt

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is state of the art that muscle contraction dynamics is adequately described by a hyperbolic relation between muscle force and contraction velocity (Hill relation), thereby neglecting muscle internal mass inertia (first-order dynamics). Accordingly, the vast majority of modelling approaches also neglect muscle internal inertia. Assuming that such first-order contraction dynamics yet interacts with muscle internal mass distribution, this study investigates two questions: (i) what is the time scale on which the muscle responds to a force step? (ii) How does this response scale with muscle design parameters? Thereto, we simulated accelerated contractions of alternating sequences of Hill-type contractile elements and point masses. We found that in a typical small muscle the force levels off after about 0.2 ms, contraction velocity after about 0.5 ms. In an upscaled version representing bigger mammals' muscles, the force levels off after about 20 ms, and the theoretically expected maximum contraction velocity is not reached. We conclude (i) that it may be indispensable to introduce second-order contributions into muscle models to understand high-frequency muscle responses, particularly in bigger muscles. Additionally, (ii) constructing more elaborate measuring devices seems to be worthwhile to distinguish viscoelastic and inertia properties in rapid contractile responses of muscles.

Indexed as

Muscle ContractionAlgorithmsAnimalsBiomechanical PhenomenaComputer SimulationElasticityFinite Element AnalysisHumansIsometric ContractionModels, TheoreticalMusclesOscillometryStress, MechanicalViscosity

Identifiers

PMID23227110
PMCPMC3512296

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.