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Muscle torque generators in multibody dynamic simulations of optimal sports performance

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Abstract

Using detailed musculoskeletal models in computer simulations of human movement can provide insights into individual muscle and joint loading; however, these muscle models increase problem dimensionality and require difficult-to-fit parameters. Here, we provide a brief overview of a muscle model alternative, muscle torque generators (MTGs), and highlight how MTG functions have been used by researchers to generate accurate dynamic simulations of optimal sports performance. Multibody dynamic models of a golf drive, track cycling, and wheelchair propulsion were designed and actuated using MTGs. Each MTG was effectively a rotational, single muscle equivalent that contained joint angle/velocity scaling and passive elements to mimic Hill-type muscle model behaviour. Optimal control algorithms were used to predict how each model would execute their respective sports task; these results were compared against experimental data collected from elite athletes. Good agreement between simulated and experimental movement trajectories was observed, with relatively low computational times required for convergence of the MTG-driven multibody simulations.

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Acknowledgements

This research was funded by McPhee’s Tier I Canada Research Chair in System Dynamics. Additional thanks for experimental participation and data collection by i) PING Inc., ii) Mike Patton and Will George of Cycling Canada, members of the Canadian track cycling team, and iii) Canadian Sports Institute Ontario.

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  1. Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada

    Keaton A. Inkol, Colin Brown, William McNally, Conor Jansen & John McPhee

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  1. Keaton A. Inkol
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Inkol, K.A., Brown, C., McNally, W. et al. Muscle torque generators in multibody dynamic simulations of optimal sports performance. Multibody Syst Dyn 50, 435–452 (2020). https://doi.org/10.1007/s11044-020-09747-9

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