Mathematical model for investigating the ability of physiologically-based phenomenological models to predict in vivo muscle energetics.
This repository contains the code for the manuscript
Konno RN, Lichtwark GA, and Dick TJM. Using physiologically-based models to predict \textit{in vivo} skeletal muscle energetics. 2024. In preparation.
There are three main code files used to run the model: vanderZee2021_LichtwarkModel.py, Beck2020_LichtwarkModel.py, and Beck2022_LichtwarkModel.py. These codes are designed to predict energy use based on the experimental data from the following three papers respectively
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van der Zee, T. J., & Kuo, A. D. (2021). The high energetic cost of rapid force development in muscle. Journal of Experimental Biology, 224(9). https://doi.org/10.1242/JEB.233965/237823
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Beck, O. N., Gosyne, J., Franz, J. R., & Sawicki, G. S. (2020). Cyclically producing the same average muscle-tendon force with a smaller duty increases metabolic rate. Proceedings of the Royal Society B: Biological Sciences, 287(1933). https://doi.org/10.1098/RSPB.2020.0431
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Beck, O. N., Trejo, L. H., Schroeder, J. N., Franz, J. R., & Sawicki, G. S. (2022). Shorter muscle fascicle operating lengths increase the metabolic cost of cyclic force production. Journal of Applied Physiology, 133(3), 524–533. https://doi.org/10.1152/JAPPLPHYSIOL.00720.2021
The MuscleModel directory contains the muscle model including the mechanical (MechModel.py) and energetic (HeatModel.py) components of the model. Each of these codes are called by MuscleModel.py.
NOTE: There is an implementation of a simplified motor unit recruitment model (RecruitmentModel.py) included in MuscleModel. By default it is not used, and it is not used in the KLD 2024 manuscript. To utilize this model switch the parameter 'scale_method' from 'None' to 'fibre-act' (scales the energetic parameters based on the muscle activations).