Zhao, Y, Qian, K, Sheng, B et al. (5 more authors) (2023) Adaptive Cooperative Control Strategy for a Wrist Exoskeleton using Model-based Joint Impedance Estimation. IEEE/ASME Transactions on Mechatronics, 28 (2). pp. 748-757. ISSN 1083-4435
Abstract
Wrist rehabilitation exoskeletons have gained much attention over the last decades, striving to restore motor functions for patients with neuromuscular disorders. Electromyography signal has been employed to estimate the motion intention to achieve interactive training schemes. However, it is a challenging task to estimate the joint impedance in real time, as it is a crucial parameter for control of exoskeletons. This article proposes an adaptive cooperative control strategy for a wrist exoskeleton based on a real-time joint impedance estimation approach. By explicitly interpreting the underlying transformation in the muscular and skeletal systems, the proposed approach estimates the motion intention and the joint impedance of a human subject simultaneously without additional calibration procedures and regulates the training trajectories and assistance accordingly. Results indicate the proposed method outperforms other training protocols, including the trajectory tracking control and the fixed cooperative control. The proposed control strategy provides an additional 66.25% motion deviation when estimated joint torque increases 12.36%, which enhances the training effectiveness and the interaction safety and promotes subjects' active engagement.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 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. |
Keywords: | Adaptive cooperative control (ACC) strategy , electromyography (EMG) , joint impedance , musculoskeletal model , wrist rehabilitation robot |
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) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/S019219/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Oct 2022 13:33 |
Last Modified: | 23 May 2024 14:07 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TMECH.2022.3211671 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:192632 |