Best-compromise between mechanical energy expenditure and foot clearance predicts leading limb motion during obstacle-crossing

This study aimed to identify the control strategy of obstacle-crossing of different heights with a multi-objective optimal control technique. Twelve young healthy adults walked and crossed obstacles of three different heights while their kinematic and ground reaction force data were measured simultaneously. Obstacle-crossing was formulated as an optimal control problem with two conflicting objectives: minimization of mechanical energy expenditure and maximization of foot-obstacle clearance. The results supported the hypothesis that experimentally measured ankle trajectories and joint angles of the swing limb and the joint moments of the stance limb could be predicted by the best compromise between these objectives, which was also independent of obstacle height. This control strategy was fundamentally different from that for unobstructed gait, and appeared to be pre-programmed into the nervous system. The results will serve as baseline data and the current technique be used for identifying changes in obstacle-crossing control strategies in people at higher risk of falling.

► Multi-objective optimal control technique was used to study lower limb motion during obstacle-crossing. ► Best-compromise between minimizing mechanical energy and maximizing foot clearance predicts experimental measurements. ► The best-compromise control strategy appeared to be invariant even when the obstacle height was changed.