Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation

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 Re...

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Bibliographic Details
Published in:Robotics (Basel) 2023-11, Vol.12 (6), p.149
Main Authors: Mathavan Jeyabalan, Prem Kumar, Nehrujee, Aravind, Elias, Samuel, Magesh Kumar, M, Sujatha, S, Balasubramanian, Sivakumar
Format: Article
Language:English
Subjects:
Adaptive control
adaptive weight support
Algorithms
arm rehabilitation robot
Care and treatment
Control systems
Degrees of freedom
Design
Design and construction
Design optimization
End effectors
end-effector robot
Exoskeletons
Gravity
Human subjects
Kinematics
neurorehabilitation
Patients
Rehabilitation
Rehabilitation robots
Robots
Self alignment
Sensors
Stroke
Stroke patients
Technology application
Training
transparency
Weight
Workspace
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Summary: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, 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’s 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’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) 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.
ISSN:2218-6581
2218-6581
DOI:10.3390/robotics12060149