Human-in-the-Loop Optimization for Knee Exoskeleton Flexion Assistance
Zhipeng Wang, Baichun Wei, Zhen Ding, Jianfei Zhu, Lianpeng Zhang, Xiangduan Zeng, Chunzhi Yi
Abstract
Human-in-the-loop optimization (HILO) has been used to identify subject-specific assistive strategies and improve the performance of wearable exoskeletons. However, there is still a gap in research on HILO regarding knee exoskeleton flexion assistance. We present a HILO methodology that optimizes the flexion torque delivered by the knee exoskeleton. The cooperation mechanism of flexor and antagonist muscles assisted by the exoskeleton is first analyzed through the dynamic model. Furthermore, the online rapid metabolic evaluation function, including the electromyographic (EMG) signals of the semitendinosus (SEM) and vastus medial (VM), is designed based on the cooperative working mechanism of the antagonist muscle. The upper and lower controllers are designed respectively to realize the construction of the HILO closed-loop control system. Finally, we experimentally demonstrate the effectiveness of the HILO methodology proposed in this paper through EMG and metabolic indicators. In particular, for the knee joint, the time required to identify assistance strategies is significantly reduced by our protocol. This research will contribute to the design of fast convergence HILO methods from the perspective of human natural driving.
BibTeX
@inproceedings{ral2025_humanintheloopop,
title = {Human-in-the-Loop Optimization for Knee Exoskeleton Flexion Assistance},
author = {Zhipeng Wang and Baichun Wei and Zhen Ding and Jianfei Zhu and Lianpeng Zhang and Xiangduan Zeng and Chunzhi Yi},
booktitle = {RA-L 2025},
year = {2025}
}