During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disorders. The device transparency, support force vector direction, and attachment to the harness vary widely across existing robotic BWS devices, but the influence of these factors on the production of gait remains unknown. Because this information is key to designing an optimal BWS, we systematically studied these determinants in this work. We report that with a highly transparent device and a conventional harness, healthy participants select a small backward force when asked for optimal BWS conditions. This unexpected finding challenges the view that during human-robot interactions, humans predominantly optimize energy efficiency. Instead, they might seek to increase their feeling of stability and safety. We also demonstrate that the location of the attachment points on the harness strongly affects gait patterns, yet harness attachment is hardly reported in literature. Our results establish principles for the design of BWS devices and personalization of BWS settings for gait neurorehabilitation.

中文翻译：

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被忽视的物理人机交互可以解释步态神经康复研究中的可变结果

在步态神经康复期间，许多因素会影响步态模式的质量，尤其是所选的体重支持 (BWS) 装置。因此，机器人 BWS 设备在神经系统疾病患者的步态康复中发挥着关键作用。现有机器人 BWS 设备的设备透明度、支持力矢量方向和与线束的连接差异很大，但这些因素对步态产生的影响仍然未知。因为这些信息是设计最佳 BWS 的关键，所以我们在这项工作中系统地研究了这些决定因素。我们报告说，使用高度透明的设备和传统的安全带，健康的参与者在被问及最佳 BWS 条件时会选择一个小的向后力。这一出乎意料的发现挑战了在人机交互过程中，人类主要优化能源效率。相反，他们可能会寻求增加他们的稳定感和安全感。我们还证明了安全带上连接点的位置强烈影响步态模式，但文献中几乎没有报道安全带连接。我们的结果为步态神经康复的 BWS 设备设计和 BWS 设置的个性化建立了原则。