Zhang, M, McDaid, A, Zhang, S et al. (2 more authors) (2019) Automated robot-assisted assessment for wrist active ranges of motion. Medical Engineering and Physics, 71. pp. 98-101. ISSN 1350-4533
Abstract
The measurement of wrist active range of motion (ROM) is essential for determining the progress of hand functional recovery, which can provide insight into quantitative improvements and enable effective monitoring during hand rehabilitation. Compared with manual methods, which depend on the experience of the therapist, the proposed robot-assisted assessment technique can measure active ROM of human wrists. The robot with a reconfigurable handle design allows for multiple wrist motions. Experiments were conducted with 11 human subjects to measure ROMs of human wrist flexion/extension and radial/ulnar deviation. Reliability analysis was conducted by calculating the intra-class correlation coefficients (ICC), standard error of measurement (SEM) and SEM%. Results showed high reliability (ICC2,1 ≥ 0.89, SEM ≤ 2.36°, SEM% ≤ 6.81%). Future will focus on adaptive joint self-alignment design between human users and robots to further improve its assessment accuracy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Published by Elsevier Ltd on behalf of IPEM. This is an author produced version of a article published in Medical Engineering & Physics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Robot-assisted; Assessment; Wrist; Active range of motion; Admittance |
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 EP/S019219/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Sep 2019 13:52 |
Last Modified: | 15 Jul 2020 00:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.medengphy.2019.07.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150305 |