Meng, W orcid.org/0000-0003-0209-8753, Zhu, C, Zuo, J et al. (3 more authors) (2019) Design and modelling of a compliant ankle rehabilitation robot redundantly driven by pneumatic muscles. In: 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 08-12 Jul 2019, Hong Kong. IEEE , pp. 459-464. ISBN 9781728124933
Abstract
Ankle sprains are the most common type of ankle injuries for the general public. Due to the lack of human manual therapy resources, it is highly demanding for robot-assisted rehabilitation training. However, most of the current robotic ankle rehab devices are driven by rigid actuators and have problems such as limited degrees of freedom, lack of safety and compliance and poor flexibility. This paper will design a new version of compliant ankle rehabilitation robot redundantly driven by pneumatic muscles (PMs) to provide full range of motion and torque ability for human ankle with enhanced safety and adaptability, attributing to the PM's high power/mass ratio, good flexibility and light weight advantages. In this paper, the driving characteristics of the PM actuators, as well as the kinematics and rehabilitation requirements of the ankle joint are analyzed. A new type of ankle rehabilitation robot that is redundantly driven by five PMs is designed and modeled. The ankle joint can be compliantly driven by the robot with full three degrees of freedom to perform dorsiflexion/plantarflexion, inversion/ eversion and adduction/abduction training. Then the kinematics and dynamics model of the rehabilitation robot is established to validate and verify the design and the models.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©2019 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. |
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 Royal Society ICA\R1\180203 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Dec 2019 12:38 |
Last Modified: | 04 Dec 2019 12:38 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/AIM.2019.8868903 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154168 |