Bayesian Optimisation of Exoskeleton Design Parameters

Daniel F. N. Gordon, Takamitsu Matsubara, Tomoyuki Noda, Tatsuya Teramae, Jun Morimoto, Sethu Vijayakumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.
Original languageEnglish
Title of host publication2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)978-1-5386-8183-1
ISBN (Print)978-1-5386-8184-8
Publication statusPublished - 11 Oct 2018
Event7th IEEE International Conference on Biomedical Robotics and Biomechatronics - Enschede, Netherlands
Duration: 26 Aug 201829 Aug 2018

Publication series

ISSN (Print)2155-1774
ISSN (Electronic)2155-1782


Conference7th IEEE International Conference on Biomedical Robotics and Biomechatronics
Abbreviated titleBiorob 2018
Internet address


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