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dc.contributor.authorMichaud, F.*
dc.contributor.authorFrey-Law, L.A.*
dc.contributor.authorLugrís, U.*
dc.contributor.authorCuadrado, L.*
dc.contributor.authorFigueroa Rodríguez, Jesús *
dc.contributor.authorCuadrado, J.*
dc.date.accessioned2025-09-08T09:14:58Z
dc.date.available2025-09-08T09:14:58Z
dc.date.issued2023
dc.identifier.citationMichaud F, Frey-Law LA, Lugrís U, Cuadrado L, Figueroa-Rodríguez J, Cuadrado J. Applying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study. Frontiers in Physiology. 2023;14.
dc.identifier.issn1664-042X
dc.identifier.otherhttps://portalcientifico.sergas.gal//documentos/647346e5c0b3b13849988650
dc.identifier.urihttp://hdl.handle.net/20.500.11940/21095
dc.description.abstractIntroduction: 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.
dc.description.sponsorshipThis work was funded by the Spanish MICIU under project PGC 2018-095145-B-I00, co-financed by the EU through the EFRD program, and by the Galician Government under grant ED431C2019/29. Moreover, FM would like to acknowledge the support of the Galician Government and the Ferrol Industrial Campus by means of the postdoctoral research contract 2022/CP/048.
dc.languageeng
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleApplying a muscle fatigue model when optimizing load-sharing between muscles for short-duration high-intensity exercise: A preliminary study
dc.typeArtigo
dc.authorsophosMichaud, F.; Frey-Law, L.A.; Lugrís, U.; Cuadrado, L.; Figueroa-Rodríguez, J.; Cuadrado, J.
dc.identifier.doi10.3389/fphys.2023.1167748
dc.identifier.sophos647346e5c0b3b13849988650
dc.journal.titleFrontiers in Physiology*
dc.organizationServizo Galego de Saúde::Áreas Sanitarias (A.S.) - Complexo Hospitalario Universitario de Santiago::Medicina física e rehabilitación
dc.relation.projectIDSpanish MICIU [PGC 2018-095145-B-I00]
dc.relation.projectIDEU through the EFRD program
dc.relation.projectIDGalician Government [ED431C2019/29]
dc.relation.projectIDFerrol Industrial Campus [2022/CP/048]
dc.relation.publisherversionhttps://doi.org/10.3389/fphys.2023.1167748
dc.rights.accessRightsopenAccess*
dc.subject.keywordAS Santiago
dc.subject.keywordCHUS
dc.typefidesArtículo Científico (incluye Original, Original breve, Revisión Sistemática y Meta-análisis)
dc.typesophosArtículo Original
dc.volume.number14


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