{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:22:48Z","timestamp":1771514568834,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T00:00:00Z","timestamp":1699315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Portescap CSR funding","award":["CR1819MEE002PPIPSUJA"],"award-info":[{"award-number":["CR1819MEE002PPIPSUJA"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Traditional end-effector robots for arm rehabilitation are usually attached at the hand, primarily focusing on coordinated multi-joint training. Therapy at an individual joint level of the arm for severely impaired stroke survivors is not always possible with existing end-effector robots. The Arm Rehabilitation Robot (AREBO)\u2014an end-effector robot\u2014was designed to provide both single and multi-joint assisted training while retaining the advantages of traditional end-effector robots, such as ease of use, compactness and portability, and potential cost-effectiveness (compared to exoskeletons). This work presents the design, optimization, and characterization of AREBO for training single-joint movements of the arm. AREBO has three actuated and three unactuated degrees of freedom, allowing it to apply forces in any arbitrary direction at its endpoint and self-align to arbitrary orientations within its workspace. AREBO\u2019s link lengths were optimized to maximize its workspace and manipulability. AREBO provides single-joint training in both unassisted and adaptive weight support modes using a human arm model to estimate the human arm\u2019s kinematics and dynamics without using additional sensors. The characterization of the robot\u2019s controller and the algorithm for estimating the human arm parameters were performed using a two degrees of freedom mechatronic model of the human shoulder joint. The results demonstrate that (a) the movements of the human arm can be estimated using a model of the human arm and robot\u2019s kinematics, (b) AREBO has similar transparency to that of existing arm therapy robots in the literature, and (c) the adaptive weight support mode control can adapt to different levels of impairment in the arm. This work demonstrates how an appropriately designed end-effector robot can be used for single-joint training, which can be easily extended to multi-joint training. Future work will focus on the evaluation of the system on patients with any neurological condition requiring arm training.<\/jats:p>","DOI":"10.3390\/robotics12060149","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T01:54:30Z","timestamp":1699408470000},"page":"149","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1759-2516","authenticated-orcid":false,"given":"Prem Kumar","family":"Mathavan Jeyabalan","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7972-0120","authenticated-orcid":false,"given":"Aravind","family":"Nehrujee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India"},{"name":"Department of Bioengineering, Christian Medical College Vellore, Vellore 632002, Tamil Nadu, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5073-0894","authenticated-orcid":false,"given":"Samuel","family":"Elias","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, Christian Medical College Vellore, Vellore 632002, Tamil Nadu, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8540-2197","authenticated-orcid":false,"given":"M.","family":"Magesh Kumar","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3456-1220","authenticated-orcid":false,"given":"S.","family":"Sujatha","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5915-1346","authenticated-orcid":false,"given":"Sivakumar","family":"Balasubramanian","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, Christian Medical College Vellore, Vellore 632002, Tamil Nadu, India"},{"name":"School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, QLD 4067, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1177\/17474930211065917","article-title":"World Stroke Organization (WSO): Global Stroke Fact Sheet 2022","volume":"17","author":"Feigin","year":"2022","journal-title":"Int. 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