Mathavan Jeyabalan, P.K.; Nehrujee, A.; Elias, S.; Magesh Kumar, M.; Sujatha, S.; Balasubramanian, S. Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation. Robotics2023, 12, 149.
Mathavan Jeyabalan, P.K.; Nehrujee, A.; Elias, S.; Magesh Kumar, M.; Sujatha, S.; Balasubramanian, S. Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation. Robotics 2023, 12, 149.
Mathavan Jeyabalan, P.K.; Nehrujee, A.; Elias, S.; Magesh Kumar, M.; Sujatha, S.; Balasubramanian, S. Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation. Robotics2023, 12, 149.
Mathavan Jeyabalan, P.K.; Nehrujee, A.; Elias, S.; Magesh Kumar, M.; Sujatha, S.; Balasubramanian, S. Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation. Robotics 2023, 12, 149.
Abstract
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)—an end-effector robot—was designed to provide both single and multi-joint assisted training while retaining the advantages of traditional end-effector robots, such as ease of use and cost-effectiveness (compared to exoskeletons). This work presents the design, optimization, and characterization of AREBO for training single-joint movements of the arm. The 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. The AREBO’s link lengths were optimized to maximize its workspace and manipulability. The AREBO provides single-joint training in both unassisted and adaptive weight support modes using a human arm model to estimate the human arm's kinematics and dynamics without using additional sensors. The characterization of the robot’s 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’s kinematics, (b) the 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.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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