Foot-Ground Contact Model Personalization Improves Tracking of a Subject’s Clinically Relevant Kinematics and Kinetics

Musculoskeletal modeling researchers aim for the ability to design personalized treatments for movement impairments. Though personalized treatments are best designed with personalized models, predictive gait simulations usually do not include foot-ground contact (FGC) model personalization. This study evaluates how FGC model personalization contributes to the accuracy of tracking experimental data in dynamically consistent gait simulations. Although overall tracking errors were similar regardless of whether FGC models were personalized, there were significant differences in foot kinematics and frontal plane joint moments for the leg on the paretic side, and FGC model personalization decreased the convergence time of the simulation. Using personalized FGC models is both more efficient and more accurate for clinically relevant quantities.