Meng, W, Zhu, Y, Zhou, Z et al. (2 more authors) (2014) Active interaction control of a rehabilitation robot based on motion recognition and adaptive impedance control. In: Proceedings of the 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 06-11 Jul 2014, Beijing, China. Institute of Electrical and Electronics Engineers , pp. 1436-1441. ISBN 9781479920747
Abstract
Although electromyography (EMG) signals and interaction force have been widely used in patient cooperative or interactive training, the conventional EMG based control usually breaks the process into a patient-driven phase and a separate passive phase, which is not desirable. In this research, an active interaction controller based on motion recognition and adaptive impedance control is proposed and implemented on a six-DOFs parallel robot for lower limb rehabilitation. The root mean square (RMS) features of EMG signals integrating with the support vector machine (SVM) classifier were used to online predict the lower limb intention in advance and to trigger the robot assistance. The impedance control strategy was adopted to directly influence the robot assistance velocity and allow the exercise to follow a physiological trajectory. Moreover, an adaptive scheme learned the muscle activity level in real time and adapted the robot impedance in accordance with patient's voluntary participation efforts. Experimental results on several healthy subjects demonstrated that the lower limb motion intention can be precisely predicted in advance, and the robot assistance mode was also adjustable based on human-robot interaction and muscle activity level of subjects. Comparing with the conventional EMG-triggered assistance methods, such a strategy can increase patient's motivation because the subject's movement intention, active efforts as well as the muscle activity level changes can be directly reflected in the trajectory pattern and the robot assistance speeds.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 IEEE. This is an author produced version of a paper accepted for publication in Proceedings of the 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | rehabilitation robot; EMG; motion recognition; impedance control; active interaction control |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Jul 2018 09:52 |
Last Modified: | 10 Jul 2018 09:52 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/FUZZ-IEEE.2014.6891705 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:125853 |