Human-Robot Cooperative Strength Training Based on Robust Admittance Control Strategy.

Area of Science:

• Biomedical Engineering
• Rehabilitation Robotics
• Biomechanics

Background:

• Stroke frequently causes lower limb motor dysfunction in the elderly.
• Existing lower limb rehabilitation robots often neglect knee soft tissue protection.
• Effective muscle strengthening is crucial for stroke recovery.

Purpose of the Study:

• To propose a human-robot cooperative lower limb active strength training system.
• To enhance knee soft tissue protection during rehabilitation exercises.
• To improve quadriceps femoris muscle stimulation in stroke survivors.

Main Methods:

• Developed a robust admittance control strategy with real-time stiffness adjustment based on knee biomechanics.
• Implemented a dual input robust controller to mitigate disturbances from model uncertainty and external noise.
• Conducted experiments with eight stroke survivors to evaluate controller performance and training feasibility.

Main Results:

• The controller effectively modulated interaction forces, reducing the risk of knee soft tissue injury.
• The system demonstrated robust tracking performance despite disturbances.
• Muscle electrical signals and interaction forces confirmed enhanced quadriceps femoris muscle stimulation.

Conclusions:

• The proposed admittance control strategy provides effective knee soft tissue protection during lower limb strength training.
• Human-robot cooperative training with this system is a feasible and safe rehabilitation method for stroke survivors.
• The technology enhances quadriceps stimulation, contributing to improved functional recovery.