Self-Balancing Exoskeleton Robots Designed to Facilitate Multiple Rehabilitation Training Movements

Area of Science:

• Biomedical Engineering
• Rehabilitation Robotics
• Biomechanics

Background:

• Traditional rehabilitation often requires assistive devices like crutches.
• Existing exoskeletons may lack adaptability to individual patient parameters.
• Need for advanced robotic systems to support diverse rehabilitation movements.

Purpose of the Study:

• To present the biomimetic design and controller of AutoLEE-II, a self-balancing exoskeleton.
• To enable patients to perform multiple rehabilitation movements without external support.
• To develop a controller adaptable to varying patient physical parameters.

Main Methods:

• Biomimetic structural design based on human anatomy, optimizing Center of Mass (CoM) and eliminating axis deviation.
• Development of a physical parameter-independent controller utilizing CoM modification.
• Exoskeleton-assisted rehabilitation training (squatting, tilting, walking) with five subjects.
• Electromyography (EMG) analysis to assess muscle activity reduction.

Main Results:

• AutoLEE-II successfully assisted patients in diverse rehabilitation exercises, including squatting, tilting, and walking.
• The exoskeleton enabled patients to maintain balance during training.
• EMG data indicated a significant reduction (approx. 20-30%) in lower limb muscle activity.

Conclusions:

• The AutoLEE-II exoskeleton effectively supports rehabilitation by enhancing balance and reducing muscular effort.
• The biomimetic design and adaptive controller allow for versatile application across different patients.
• This technology holds promise for improving the efficacy and accessibility of physical rehabilitation.