A Linear Rehabilitative Motion Planning Method with a Multi-Posture Lower-Limb Rehabilitation Robot

Area of Science:

• Robotics
• Rehabilitation Medicine
• Biomechanics

Background:

• Physicians currently plan lower-limb exercises using linear guidance, focusing on patient-specific paths and smooth trajectories to minimize jerks.
• Replicating the precision of human-guided rehabilitation in robotic systems presents a significant challenge.

Purpose of the Study:

• To introduce a linear rehabilitation motion planning method for physicians using a multi-posture lower-limb rehabilitation robot.
• To develop a system for both path and trajectory planning that correlates linear trajectories with key joint rehabilitation metrics.

Main Methods:

• The lower limb's action space was subdivided into four training sections and classified to define the relationship between linear trajectories and joint rehabilitation metrics.
• A rehabilitative path generation system was developed based on joint rehabilitation indicators.
• High-order polynomial curves were used for smooth trajectory continuity, and trajectory planning was refined using constrained quadratic optimization to minimize jerks.

Main Results:

• Optimized trajectories were compared with randomly generated ones, showing the suitability of trajectory optimization for real-time planning.
• Trajectories generated using two groups of joint rehabilitation indicators were compared, demonstrating the system's effectiveness.
• The proposed path generation system assists clinicians in efficient and precise robot-assisted rehabilitation path planning.

Conclusions:

• The developed linear rehabilitation motion planning method effectively addresses the challenge of replicating physician precision in robotic systems.
• The system facilitates efficient and precise robot-assisted rehabilitation path planning, enhancing patient care.
• Trajectory optimization is suitable for real-time rehabilitation planning, improving safety and efficacy.