Dynamic optimization of Gait with a Generalized Lower-Limb Prosthesis Model

Predictive simulation of gait is a promising tool for robotic lower limb prosthesis design, but has been limited in its application to models of existing design types. We propose a modeling approach to find optimal prosthesis dynamics in gait simulations without constraining the prosthesis to follow kinematics allowed by a specific joint mechanism. To accomplish this, we render a transtibial prosthetic device as the composition of its resultant forces and moments as they act upon the prosthetic foot and socket and allow 3 degree-of-freedom planar motion. The model is implemented into a human musculoskeletal model and used to solve dynamic optimizations of muscle and prosthesis controls to minimize muscle effort and loading on the residual limb during walking. The emphasis on muscle effort vs. limb loading is varied in the minimization objective and the resulting optimal prosthesis dynamics are compared. We found that muscle effort and socket loading measures were reduced for our prosthesis model compared to a revolute joint prosthesis model. We interpret large displacements in the linear axes to transfer energy to the plantarflexion action before toe-off and reduce loading at the socket-limb interface. Our results suggest this approach could assist in the design of non-biomimetic prostheses but requires experimental validation to assess our modeling assumptions, as well as progress toward increased fidelity of predictive simulation approaches more generally.