Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Front Physiol. 2024 Mar 11:15:1366172. doi: 10.3389/fphys.2024.1366172. eCollection 2024.

Abstract

Introduction: Computational muscle force models aim to mathematically represent the mechanics of movement and the factors influencing force generation. These tools allow the prediction of the nonlinear and task-related muscle behavior, aiding biomechanics, sports science, and rehabilitation. Despite often overlooking muscle fatigue in low-force scenarios, these simulations are crucial for high-intensity activities where fatigue and force loss play a significant role. Applications include functional electrical stimulation, motor control, and ergonomic considerations in diverse contexts, encompassing rehabilitation and the prevention of injuries in sports and workplaces. Methods: In this work, the authors enhance the pre-existing 3CCr muscle fatigue model by introducing an additional component of force decay associated with central fatigue and a long-term fatigue state. The innovative four-compartment model distinguishes between the short-term fatigued state (related to metabolic inhibition) and the long-term fatigued state (emulating central fatigue and potential microtraumas). Results: Its validation process involved experimental measurements during both short- and long-duration exercises, shedding light on the limitations of the traditional 3CCr in addressing dynamic force profiles.

Keywords: ergonomics; force prediction; mathematical models; muscle fatigue model; muscle force; musculotendon dynamics; musculotendon model; sport performance.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Grant PID2022-140062OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, by the European Union. Grant ED431C 2023/01 by the Galician Government. 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.