Our approach introduces a novel framework and showcases its application in solving predictive models. Leveraging opensource tools, including OpenSim and Blender, we built the FES cycling model. Subsequently, we outlined two predictive problems within OpenSim Moco: (P1) moving from point A to point B with different crank resistances, and (P2) tracking target speeds. Our study reveals the successful convergence of these simulations, showcasing the integrated framework’s robustness and efficiency in overcoming previous limitations. Indeed, the presented solution addresses the need for multiple simulations.  View License

With this project, we investigated the use of passive knee orthoses for FES cycling assistance. Hence, we compared the cycling cadence and quadriceps excitation using an FES cycling simulation platform for different spring torques and ranges.  View License

Basic framework for FES cycling in OpenSim and its integration with matlab.  View License