In this repository, we present a series of advanced control strategies to simulate forward dynamics in muscle-driven biomechanical models using OpenSim. Our work builds upon prior research on lower-limb rehabilitation for spinal cord injuries and motor disorders, introducing enhanced computational tools for more accurate and efficient simulations. By leveraging experimental data from able-bodied subjects during slow-speed walking, we developed different controllers, comparing their effectiveness to traditional methods involving active orthoses and functional electrical stimulation (FES). The results demonstrate improved accuracy in controlling knee motion with errors under five degrees and the capability to analyse gait dynamics at very slow speeds, offering promising avenues for enhancing therapy outcomes and reducing therapists' physical burden.

This repository has been reorganised and updated to incorporate the latest features of OpenSim 4.5, along with Python scripts specifically designed for forward dynamics simulations. These updates enhance the functionality and user experience, aligning with current computational methodologies in biomechanical research.