Data for "Muscle synergy priors enhance biomechanical fidelity in predictive musculoskeletal locomotion simulation"

This research evaluates the efficacy of a physiology-informed reinforcement learning framework that constrains control to a low-dimensional muscle-synergy basis in predicting human-like locomotion. It compares the synergistic controller against an unconstrained independent controller by evaluating their ability to reproduce condition-dependent gait kinematics, joint kinetics, ground reaction forces, and muscle activation patterns across varying speeds and slopes.