Bayesian Optimisation of Exoskeleton Design Parameters
Bayesian Optimisation of Exoskeleton Design Parameters
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外骨骼设计参数的贝叶斯优化
DOI：
10.1109/biorob.2018.8487720
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
S. Vijayakumar
中科院分区：
文献类型：
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作者：
Daniel F. N. Gordon;Takamitsu Matsubara;T. Noda;T. Teramae;J. Morimoto;S. Vijayakumar
目前正在开发外骨骼，并将其用作有效的康复工具。外骨骼附着点的理想位置和设计可能会因穿戴者的物理尺寸，康复或辅助的肌肉或关节的目标，或人体受试者与外骨骼设备之间存在关节错位等因素而有所不同。在本文中，我们提出了一种基于人在环优化过程来确定理想外骨骼袖带位置的方法，并对我们的方法进行了实证验证。在XoR外骨骼（ATR，日本）的帮助下，受试者在一系列袖带配置下行走时测量肌肉活动。采用贝叶斯优化过程并进行测试，以确定XoR套管的最佳配置，从而最大限度地减少测量的肌电活动。与线性搜索相比，该方法能更有效地识别出异位差的最佳设计参数。
Exoskeletons are currently being developed and used as effective tools for rehabilitation. The ideal location and design of exoskeleton attachment points can vary due to factors such as the physical dimensions of the wearer, which muscles or joints are targeted for rehabilitation or assistance, or the presence of joint misalignment between the human subject and exoskeleton device. In this paper, we propose an approach for identifying the ideal exoskeleton cuff locations based on a human-in-the-Ioop optimisation process, and present an empirical validation of our method. The muscle activity of a subject was measured while walking with assistance from the XoR exoskeleton (ATR, Japan) over a range of cuff configurations. A Bayesian optimisation process was implemented and tested to identify the optimal configuration of the XoR cuffs which minimised the measured EMG activity. Using this process, the optimal design parameters for the XoR were identified more efficiently than via linear search.