Verification of a 3D Predictive Gait Simulation Framework Using Physiologically Based Objective Functions

Abstract

Research on 3D predictive gait simulation remains limited. This study therefore verifies an existing 3D predictive gait simulation framework implemented in SCONE, with the goal that this verified framework can serve as a physiologically plausible modelling and optimisation platform for future related studies. Four optimisation criteria were selected, namely minimising cost of transport, minimising muscle activity, maxmising head instability, and minimising foot-ground impact. These criteria were combined to form a set of objective functions, under which the framework was optimised. The predicted results produced by each objective function were quantitatively compared with experimental data using Pearson r and RMSE/SD, and agreement was evaluated across multiple biomechanical categories, including joint kinematics, ground reaction forces, joint moments and joint powers. The results indicate that, under the optimal objective function, the predictive performance approaches that of the ExpTrack solution that directly tracks experimental data. The framework reproduces sagittal plane hip, knee and ankle angles, vertical and anterior-posterior ground reaction forces, all joint moments and ankle power with strong agreement, but agreement is weaker for hip adduction, medio-lateral ground reaction force, and knee and hip power. Overall, these findings demonstrate the strengths of the framework in reproducing experimental 3D gait, while also revealing limitations in medio-lateral stability control and in the current model and controller settings, providing a basis for targeted improvements in future work.