Institute of Biomedical Engineering, National Taiwan University, Taiwan.
Gait Posture. 2012 Jul;36(3):552-6. doi: 10.1016/j.gaitpost.2012.05.012. Epub 2012 Jun 30.
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.
本研究旨在采用多目标最优控制技术确定跨越不同高度障碍物的控制策略。十二名年轻健康的成年人在行走并跨越三种不同高度的障碍物时，同步测量其运动学和地面反力数据。将障碍物跨越问题表述为一个具有两个冲突目标的最优控制问题：最小化机械能消耗和最大化足-障碍物间隙。研究结果支持了以下假设：通过在这些目标之间进行最佳折衷，可以预测实验测量的踝关节轨迹和摆动肢体的关节角度以及支撑肢体的关节力矩，而与障碍物高度无关。这种控制策略与无障碍步态的控制策略有根本的不同，似乎是预先编程到神经系统中的。研究结果将作为基准数据，当前的技术可用于识别跌倒风险较高人群中跨越障碍物控制策略的变化。
