Muscle-driven simulations of cycling using optimal control methods and experimental data for 16 participants.
The aim of this work was to develop and validate a set of muscle-driven simulations of cycling using optimal control methods. We used direct collocation to generate simulations of 16 participants cycling over a range of powers (40-216 W) and cadences (75-99 RPM) using two optimization objectives: a baseline objective that minimized muscle effort and a second objective that additionally minimized tibiofemoral joint forces. Adding a term in the objective function to minimize tibiofemoral forces preserved cycling power and kinematics, improved similarity between active muscle force timing and experimental electromyography, and decreased tibiofemoral joint reaction forces, which better matched previously reported in vivo measurements.
•Read our paper: https://doi.org/10.1038/s41598-023-47945-5
•Download the data, models, and code:
--Motion capture, external force, kinematic, and joint states data for 3 full minutes of cycling
--Moco simulation code with example scripts to run the code
--Example results files