Human Gait Cost Function Varies with Walking Speed: An Inverse Optimal Control Study

This work investigates the optimal cost function 1 composition for human gait at different walking speeds. Kine- 2 matic and kinetic data for walking at four walking speeds 3 were collected from five able-bodied individuals. The data was 4 then used to recover optimal cost functions in a predictive 5 simulation environment with musculoskeletal models. 20 inverse 6 optimal control (IOC) problems were solved for cost function 7 weight tuning using the previously developed and validated 8 Adaptive Reference IOC (AR-IOC) algorithm. Given the walking 9 speed range examined (0.6-1.5m/s), the converged cost function 10 weights suggest that the increase in walking speed attributes to 11 a reduction of foot sliding penalty weight and weight increase 12 for the center of mass (CoM) acceleration and stability as 13 confirmed by several experiments. Furthermore, we did not 14 observe any significant weight shift in effort reduction between 15 the upper and the lower body with respect to walking speed. The 16 obtained results from this study can be used in a toolbox for 17 obtaining subject- and task-specific cost functions and assisting 18 the development of personalized rehabilitation technologies. 19