Evidence map›Paper›PMID 40013240›Full record

ArticleFrontiers in physiology2025

A four-compartment controller model of muscle fatigue for static and dynamic tasks.

James Yang, Ritwik Rakshit, Shuvrodeb Barman, Yujiang Xiang

Abstract read
In one paragraph

Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

James YangHuman-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, United States.
Ritwik RakshitHuman-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, United States.
Shuvrodeb BarmanSchool of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United States.
Yujiang XiangSchool of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Compartment based models of muscle fatigue have been particularly successful in accurately modeling isometric (static) tasks or actions. However, dynamic actions, which make up most everyday movements, are governed by different central and peripheral processes, and must therefore be modeled in a manner accounting for the differences in the responsible mechanisms. In the literature, a three-component controller (3CC) muscle fatigue model (MFM) has been proposed and validated for static tasks. A recent study reported a four-compartment muscle fatigue model considering both short- and long-term fatigued states. However, neither has been validated for both static and dynamic tasks. Methods: In this work we proposed a new four-compartment controller model of muscle fatigue with enhanced recovery (4CCr) that allows the modeling of central and peripheral fatigue separately and estimates strength decline for static and dynamic tasks. Joint velocity was used as an indicator of the degree of contribution of either mechanism. Model parameters were estimated from part of the experimental data and finally, the model was validated through the rest of experimental data that were not used for parameter estimation. Results: The 3CC model cannot capture the fatigue phenomenon that the velocity of contraction would affect isometric strength measurements as shown in experimental data. The new 4CCr model maintains the predictions of the extensively validated 3CC model for static tasks but provides divergent predictions for isokinetic activities (increasing fatigue with increasing velocity) in line with experimentally observed trends. This new 4CCr model can be extended to various domains such as individual muscle fatigue, motor units' fatigue, and joint-based fatigue.

Indexed as

central fatiguecompartment theoryisokinetic tasksisometric tasksmuscle fatigue modelperipheral fatigue

Identifiers

PMID40013240
PMCPMC11861306

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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.