학술논문

Bayesian Optimisation of Exoskeleton Design Parameters
Document Type
Conference
Source
2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) Biomedical Robotics and Biomechatronics (Biorob), 2018 7th IEEE International Conference on. :653-658 Aug, 2018
Subject
Bioengineering
Robotics and Control Systems
Exoskeletons
Optimization
Electromyography
Thigh
Bayes methods
Legged locomotion
Muscles
Language
ISSN
2155-1782
Abstract
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.