Fig. 2

Workflow for EMG-driven modeling with SynX (left panel with green background) and SO (right panel with orange background) as performed in this study. Both methods use experimental joint kinematics and moments as inputs and calculate muscle activations and forces such that predicted net joint moments from the musculoskeletal model closely match experimental net joint moments from inverse dynamics. However, notable differences exist in the optimization problem formulations for these two methods. For EMG-driven modeling with SynX, the design variables were time-invariant model parameter values and SynX variables, with the optimization problem being solved across all time frames together. In contrast, for SO, the design variables were time-varying muscle activations, typically utilizing model parameter values from scaled generic models or literature references, with the optimization problem being solved for each time frame separately. Muscle activations found by both approaches were used to estimate muscle forces and their respective contributions to net joint moments