Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study
Introduction: Multiple different mathematical models have been developed to represent muscle force, to represent multiple muscles in the musculoskeletal system, and to represent muscle fatigue. However, incorporating these different models together to describe the behavior of a high-intensity exerci...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2023.1167748/full |
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| author | Florian Michaud Laura A. Frey-Law Urbano Lugrís Lucía Cuadrado Jesús Figueroa-Rodríguez Javier Cuadrado |
| author_facet | Florian Michaud Laura A. Frey-Law Urbano Lugrís Lucía Cuadrado Jesús Figueroa-Rodríguez Javier Cuadrado |
| author_sort | Florian Michaud |
| collection | DOAJ |
| description | Introduction: Multiple different mathematical models have been developed to represent muscle force, to represent multiple muscles in the musculoskeletal system, and to represent muscle fatigue. However, incorporating these different models together to describe the behavior of a high-intensity exercise has not been well described.Methods: In this work, we adapted the three-compartment controller (3CCr) muscle fatigue model to be implemented with an inverse-dynamics based optimization algorithm for the muscle recruitment problem for 7 elbow muscles to model a benchmark case: elbow flexion/extension moments. We highlight the difficulties in achieving an accurate subject-specific approach for this multi-level modeling problem, considering different muscular models, compared with experimental measurements. Both an isometric effort and a dynamic bicep curl were considered, where muscle activity and resting periods were simulated to obtain the fatigue behavior. Muscle parameter correction, scaling and calibration are addressed in this study. Moreover, fiber-type recruitment hierarchy in force generation was added to the optimization problem, thus offering an additional novel muscle modeling criterion.Results: It was observed that: i) the results were most accurate for the static case; ii) insufficient torque was predicted by the model at some time points for the dynamic case, which benefitted from a more precise calibration of muscle parameters; iii) modeling the effects of muscular potentiation may be important; and iv) for this multilevel model approach, the 3CCr model had to be modified to avoid reaching situations of unrealistic constant fatigue in high intensity exercise-resting cycles.Discussion: All the methods yield reasonable estimations, but the complexity of obtaining accurate subject-specific human models is highlighted in this study. The proposed novel muscle modeling and force recruitment criterion, which consider the muscular fiber-type distinction, show interesting preliminary results. |
| first_indexed | 2024-04-09T16:10:15Z |
| format | Article |
| id | doaj.art-bb89454c91164f8cb2ee7d1ee2fdff04 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-04-09T16:10:15Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-bb89454c91164f8cb2ee7d1ee2fdff042023-04-24T11:24:30ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2023-04-011410.3389/fphys.2023.11677481167748Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary studyFlorian Michaud0Laura A. Frey-Law1Urbano Lugrís2Lucía Cuadrado3Jesús Figueroa-Rodríguez4Javier Cuadrado5Laboratory of Mechanical Engineering, Campus Industrial de Ferrol, Universidade da Coruña, Ferrol, SpainDepartment of Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, IA, United SatesLaboratory of Mechanical Engineering, Campus Industrial de Ferrol, Universidade da Coruña, Ferrol, SpainDepartment of Physical Medicine and Rehabilitation, University Hospital Complex, Santiago de Compostela, SpainDepartment of Physical Medicine and Rehabilitation, University Hospital Complex, Santiago de Compostela, SpainLaboratory of Mechanical Engineering, Campus Industrial de Ferrol, Universidade da Coruña, Ferrol, SpainIntroduction: Multiple different mathematical models have been developed to represent muscle force, to represent multiple muscles in the musculoskeletal system, and to represent muscle fatigue. However, incorporating these different models together to describe the behavior of a high-intensity exercise has not been well described.Methods: In this work, we adapted the three-compartment controller (3CCr) muscle fatigue model to be implemented with an inverse-dynamics based optimization algorithm for the muscle recruitment problem for 7 elbow muscles to model a benchmark case: elbow flexion/extension moments. We highlight the difficulties in achieving an accurate subject-specific approach for this multi-level modeling problem, considering different muscular models, compared with experimental measurements. Both an isometric effort and a dynamic bicep curl were considered, where muscle activity and resting periods were simulated to obtain the fatigue behavior. Muscle parameter correction, scaling and calibration are addressed in this study. Moreover, fiber-type recruitment hierarchy in force generation was added to the optimization problem, thus offering an additional novel muscle modeling criterion.Results: It was observed that: i) the results were most accurate for the static case; ii) insufficient torque was predicted by the model at some time points for the dynamic case, which benefitted from a more precise calibration of muscle parameters; iii) modeling the effects of muscular potentiation may be important; and iv) for this multilevel model approach, the 3CCr model had to be modified to avoid reaching situations of unrealistic constant fatigue in high intensity exercise-resting cycles.Discussion: All the methods yield reasonable estimations, but the complexity of obtaining accurate subject-specific human models is highlighted in this study. The proposed novel muscle modeling and force recruitment criterion, which consider the muscular fiber-type distinction, show interesting preliminary results.https://www.frontiersin.org/articles/10.3389/fphys.2023.1167748/fullmuscle forcemultibody dynamicsinjury preventionsport performancemuscle fatigue modelmusculotendon model |
| spellingShingle | Florian Michaud Laura A. Frey-Law Urbano Lugrís Lucía Cuadrado Jesús Figueroa-Rodríguez Javier Cuadrado Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study Frontiers in Physiology muscle force multibody dynamics injury prevention sport performance muscle fatigue model musculotendon model |
| title | Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study |
| title_full | Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study |
| title_fullStr | Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study |
| title_full_unstemmed | Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study |
| title_short | Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study |
| title_sort | applying a muscle fatigue model when optimizing load sharing between muscles for short duration high intensity exercise a preliminary study |
| topic | muscle force multibody dynamics injury prevention sport performance muscle fatigue model musculotendon model |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2023.1167748/full |
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