Energy-Optimal Human Walking With Feedback-Controlled Robotic Prostheses: A Computational Study

Abstract

Lower-limb amputees typically experience reduced mobility and higher metabolic rates than non-amputees. It may be possible to improve their mobility and metabolic rate with an optimized robotic prosthesis. Here, we use large-scale trajectory optimization on a simulated transtibial amputee with a robotic prosthesis to obtain metabolic energy-minimizing walking gaits with multiple prosthesis feedback controllers. Using such optimizations, we obtained trends in the energetics and kinematics for various prosthesis work levels. We find that the net metabolic rate has a non-monotonic relationship with the net prosthesis work rate: too much or too little prosthesis work results in higher metabolic rates. We predict that metabolic rate could be reduced below that of a non-amputee, although such gaits are highly asymmetric and not seen in experiments with amputees wearing robotic prostheses. We predict higher metabolic rates with SACH foot, a passive prosthesis. Walking gaits with left-right symmetry in kinematics or ground reaction forces have higher metabolic rates than asymmetric gaits, suggesting a potential reason for asymmetries in amputee walking. Our findings suggest that a computational framework such as the one presented here could augment the experimental approaches to prosthesis design iterations, although quantitatively accurate simulation-based prediction of experiments remains an open problem.