Can predictive simulations of walker-assisted gait using calibrated muscle models capture subject-specific walking features in individuals with spinal cord injury?

• Predictive simulations of walker-assisted gait in spinal cord injury patients. • Predictive simulations can reproduce gait metrics of spinal cord injury subjects. • Functionally-calibrated models produced more accurate lower body kinematics results. • Predicted inter-subject variability of kinematics was lower than measured one. This study aims to evaluate whether our predictive simulation framework, coupled with different musculoskeletal model personalization methods, can reproduce the distinct subject-specific gait features in individuals with spinal cord injury (SCI). To this end, motion capture data was collected from four participants. Predictive simulations of walker-assisted gait were performed using direct collocation in an optimal control problem. The cost function included terms minimizing metabolic energy rate and muscle effort, along with additional terms reflecting the instructions of the clinicians. Post-simulation analyses were carried out to perform inter-subject and intra-subject comparisons in both the experimental data and predictive simulations. The predictive simulations reproduced some distinct gait metrics for the four subjects with SCI. However, the predicted inter-subject variability of the kinematics was generally statistically lower than the experimental one. When comparing subjects pairwise, in some cases, the predictive simulations were able to capture the similarities or discrepancies in kinematics and gait metrics between two individuals. Further work is required to improve the realism of musculoskeletal models, enhance the formulation of predictive simulations, and include more subjects for achieving more generalizable results.