A four-compartment controller model of muscle fatigue for static and dynamic tasks
IntroductionCompartment 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 mode...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2025.1518847/full |
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| author | James Yang Ritwik Rakshit Shuvrodeb Barman Yujiang Xiang |
| author_facet | James Yang Ritwik Rakshit Shuvrodeb Barman Yujiang Xiang |
| author_sort | James Yang |
| collection | DOAJ |
| description | IntroductionCompartment 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.MethodsIn 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.ResultsThe 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. |
| format | Article |
| id | doaj-art-41e68980096841118f71f87ad7f83f59 |
| institution | Kabale University |
| issn | 1664-042X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Physiology |
| spelling | doaj-art-41e68980096841118f71f87ad7f83f592025-02-12T07:26:30ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2025-02-011610.3389/fphys.2025.15188471518847A four-compartment controller model of muscle fatigue for static and dynamic tasksJames Yang0Ritwik Rakshit1Shuvrodeb Barman2Yujiang Xiang3Human-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, United StatesHuman-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, United StatesSchool of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United StatesSchool of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, United StatesIntroductionCompartment 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.MethodsIn 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.ResultsThe 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.https://www.frontiersin.org/articles/10.3389/fphys.2025.1518847/fullmuscle fatigue modelisometric tasksisokinetic taskscompartment theorycentral fatigueperipheral fatigue |
| spellingShingle | James Yang Ritwik Rakshit Shuvrodeb Barman Yujiang Xiang A four-compartment controller model of muscle fatigue for static and dynamic tasks Frontiers in Physiology muscle fatigue model isometric tasks isokinetic tasks compartment theory central fatigue peripheral fatigue |
| title | A four-compartment controller model of muscle fatigue for static and dynamic tasks |
| title_full | A four-compartment controller model of muscle fatigue for static and dynamic tasks |
| title_fullStr | A four-compartment controller model of muscle fatigue for static and dynamic tasks |
| title_full_unstemmed | A four-compartment controller model of muscle fatigue for static and dynamic tasks |
| title_short | A four-compartment controller model of muscle fatigue for static and dynamic tasks |
| title_sort | four compartment controller model of muscle fatigue for static and dynamic tasks |
| topic | muscle fatigue model isometric tasks isokinetic tasks compartment theory central fatigue peripheral fatigue |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2025.1518847/full |
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