@inproceedings{e9a43f7af15b4439bfd7dfc4648f5e99,
title = "A novel sEMG control-based variable stiffness exoskeleton",
abstract = "In recent years, surface electromyography (sEMG) signals which are biomedical signals generated by muscles have been utilized to estimate human's muscular torque and predict their intention. In this paper, a variable stiffness exoskeleton which utilizes EMG signals to adjust the stiffness of the output link to meet different environmental requirements and guarantee the wearer's safety has been proposed. There is a stiffness adjustment mechanism located on the forearm part of the exoskeleton. Two dry electrodes which collect sEMG signals from agonist and antagonist muscles pair were attached on the subject's skin of corresponding muscle fibers respectively. The collected sEMG signals could be utilized to adjust the stiffness of output link according to the subject's intention. Combining sEMG signals with variable stiffness actuator (VSA) in the proposed exoskeleton, different outputs of stiffness could be realized in a compact and light hardware system. Experimental results showed the stiffness could be adjusted smoothly according to the Intention-based sEMG control.",
keywords = "Exoskeleton, Intention recognition, Surface electromyography, Variable stiffness",
author = "Yi Liu and Shuxiang Guo and Songyuan Zhang and Luc Boulardot",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 ; Conference date: 06-08-2017 Through 09-08-2017",
year = "2017",
month = aug,
day = "23",
doi = "10.1109/ICMA.2017.8016029",
language = "英语",
series = "2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1444--1449",
booktitle = "2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017",
address = "美国",
}