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机器人诱导的人类行走扰动揭示了运动适应的选择性产生。

Robot-induced perturbations of human walking reveal a selective generation of motor adaptation.

机构信息

Department of Physical Medicine and Rehabilitation, Harvard Medical School, 300 First Avenue, Charlestown, MA 02129, USA.

School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland.

出版信息

Sci Robot. 2017 May 24;2(6). doi: 10.1126/scirobotics.aam7749.

Abstract

The processes underlying the generation of motor adaptation in response to mechanical perturbations during human walking have been subject to debate. We used a robotic system to apply mechanical perturbations to step length and step height over consecutive gait cycles. Specifically, we studied perturbations affecting only step length, only step height, and step length and height in combination. Both step-length and step-height perturbations disrupt normal walking patterns, but step-length perturbations have a far greater impact on locomotor stability. We found a selective process of motor adaptation in that participants failed to adapt to step-height perturbations but strongly adapted to step-length perturbations, even when these adaptations increased metabolic cost. These results indicate that motor adaptation during human walking is primarily driven by locomotor stability, and only secondarily by energy expenditure and walking pattern preservation. These findings have substantial implications for the design of protocols for robot-assisted gait rehabilitation.

摘要

在人类行走过程中,针对机械扰动产生运动适应的背后机制一直存在争议。我们使用机器人系统在连续的步态周期中对步长和步高施加机械扰动。具体而言,我们研究了仅影响步长、仅影响步高以及同时影响步长和步高的扰动。步长和步高扰动都会破坏正常的行走模式,但步长扰动对运动稳定性的影响要大得多。我们发现了一种选择性的运动适应过程,即参与者无法适应步高扰动,但会强烈适应步长扰动,即使这些适应会增加代谢成本。这些结果表明,人类行走过程中的运动适应主要由运动稳定性驱动,其次才是能量消耗和行走模式的维持。这些发现对机器人辅助步态康复方案的设计具有重要意义。

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