Humans optimally anticipate and compensate for an uneven step during walking.
Humans optimally anticipate and compensate for an uneven step during walking.
复制标题
作者：
Darici O;Kuo AD
沿着人行道路缘行走的简单任务实际上是一个动态预测任务。路边是一种干扰，如果没有预见到并得到补偿，可能会导致动力损失。也许可以充分调整动量以确保到达时间不受干扰，但有无限种可能的方法可以做到这一点。稳定、水平的步态很大程度上是由能源经济决定的，这对于地形干扰至少应该同样重要。然而，尚不清楚经济是否也会影响走上路边，以及预期是否有所帮助。在这里，我们表明人类通过前进速度调整的预期模式进行补偿，这是通过最小化机械能输入的标准来预测的。该策略是通过双足行走动力学的简单模型的最优控制来机械预测的，每条腿的推出功作为输入。优化预测速度（以及动量）调整的三相轨迹，包括预期阶段。在实验中，人类受试者沿着预测的三相轨迹爬上人工路缘石，相对于未受干扰的平坦地面，这大致保持了整体行走速度。该轨迹包括在路缘之前加速几步，在上升时失去相当大的动力，然后在之后几步恢复速度。下降路缘需要一条几乎相反但仍可预测的速度波动轨迹，这与模型预测一致，即速度波动幅度应随路缘高度线性变化。正如模型预测的那样，随着平均速度加快，波动幅度也略有减小。人类可以推理步行的动态，以计划预期和经济的控制，即使路上有人行道路缘。
The simple task of walking up a sidewalk curb is actually a dynamic prediction task. The curb is a disturbance that could cause a loss of momentum if not anticipated and compensated for. It might be possible to adjust momentum sufficiently to ensure undisturbed time of arrival, but there are infinite possible ways to do so. Much of steady, level gait is determined by energy economy, which should be at least as important with terrain disturbances. It is, however, unknown whether economy also governs walking up a curb, and whether anticipation helps. Here, we show that humans compensate with an anticipatory pattern of forward speed adjustments, predicted by a criterion of minimizing mechanical energy input. The strategy is mechanistically predicted by optimal control for a simple model of bipedal walking dynamics, with each leg’s push-off work as input. Optimization predicts a triphasic trajectory of speed (and thus momentum) adjustments, including an anticipatory phase. In experiment, human subjects ascend an artificial curb with the predicted triphasic trajectory, which approximately conserves overall walking speed relative to undisturbed flat ground. The trajectory involves speeding up in a few steps before the curb, losing considerable momentum from ascending it, and then regaining speed in a few steps thereafter. Descending the curb entails a nearly opposite, but still anticipatory, speed fluctuation trajectory, in agreement with model predictions that speed fluctuation amplitudes should scale linearly with curb height. The fluctuation amplitudes also decrease slightly with faster average speeds, also as predicted by model. Humans can reason about the dynamics of walking to plan anticipatory and economical control, even with a sidewalk curb in the way.