Sheng, B, Meng, W, Deng, C et al. (1 more author) (2016) Model based kinematic & dynamic simulation of 6-DOF upper-limb rehabilitation robot. In: Intelligent Robot Systems (ACIRS), Asia-Pacific Conference on. Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), 20-22 Jul 2016, Tokyo, Japan. IEEE , pp. 21-25. ISBN 978-1-5090-1362-3
Abstract
Globally, a large population is suffering from motor disabilities caused by acute lesions to brain nervous system. One example is stroke, which is the third largest killer in New Zealand and the United States. Traditional manual therapy usually requires cooperative and intensive efforts from therapists and patients. Robot-assisted upper-limb rehabilitation techniques have been actively researched in the past few decades. However, limitations still exist such as inappropriate robotic modelling, mechanical design or limited Range of Motion (ROM). This paper proposes a mathematical model for a 6-Degree of Freedom (DOF) Universal Robot to be used in a rehabilitation system. This study focuses on the kinematics and dynamic analysis by using the Denavit-Hartenberg (D-H) parameters method with coordinate transformation theory. In order to simplify the computation process, Kane equation method is introduced in this paper. Simulation results show that the proposed model is correct although the fluctuation is possible to be reduced further. It concludes that the mathematical model can provide an intuitive and effective environment for designing the rehabilitation robot and planning the clinical trials.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016 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 |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jan 2018 10:07 |
Last Modified: | 19 Jan 2018 13:01 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ACIRS.2016.7556181 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:125860 |