ArticleMedical & biological engineering & computing2024
Design and analysis of a compatible exoskeleton rehabilitation robot system based on upper limb movement mechanism.
Article in Medical & biological engineering & computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- An upper-limb teleoperation exoskeleton with stepless arm-length parameterization and adaptive force-triggered impedance blending.Scientific reports · 2026Article
- Experimental Evaluation of Kinematic Compatibility in Three Upper Limb Exoskeleton Configurations Using Interface Force and Torque.Biomimetics (Basel, Switzerland) · 2026Article
- Design, development, and evaluation of a novel shoulder phantom testbed for analyzing interaction forces and reachability of wearable exoskeletons.Wearable technologies · 2025Article
- Sixty years in service to international biomedical engineering community.Medical & biological engineering & computing · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskeleton rehabilitation robot system that could realize shoulder-elbow-wrist joint rehabilitation training. Firstly, a motion equivalent model was established based on the upper limb movement mechanism, the robot mechanism configuration was designed, and the optimization algorithm and spatial mechanism theory were used to optimize and analyze the structural parameters and human-machine compatibility of the robot, which will guide the design of the robot's model. Then, the robot kinematics were solved, and its maximum motion range, dexterity distribution, and daily motion trajectory were simulated. Finally, a system prototype was built to test the maximum range of robot-assisted human upper limb training by laser tracker, while the pressure of human-machine interaction during training was captured and analyzed by flexible sensors. The results show that the proposed rehabilitation robot could nearly completely cover the range of motion of upper limb joints and meet the needs of trajectory training, and the linear velocity dexterity and angular velocity dexterity in the motion space are maximum 0.55 and 0.89, and the human-machine interaction pressures during the training process are all less than 10 kPa. Besides, this paper also conducted a system evaluation based on the fuzzy comprehensive evaluation model, and the evaluation result was 0.39, with an excellent evaluation grade, it indirectly indicates that the robot's overall performance was good.
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Registered trials
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