Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Control Systems

Background:

• Continuous passive motion (CPM) and controllable active motion (CAM) devices are crucial for joint rehabilitation.
• Existing devices often rely on mechanical resistance, limiting adaptability.
• A need exists for advanced, adaptable, and data-driven physiotherapy solutions.

Purpose of the Study:

• To present a novel computerized CPM/CAM system for joint rehabilitation.
• To eliminate the need for traditional mechanical resistance devices.
• To enable sophisticated, auto-adaptable physiotherapy with enhanced data capabilities.

Main Methods:

• Development of a PC-based CPM/CAM system controlled by online sliding-mode Fuzzy Neural Network (FNN) calculations.
• Implementation of an electric motor for active resistance, controlled via an active impedance control feedback system.
• Integration of a force sensor for real-time feedback within the FNN control loop.

Main Results:

• The system successfully generates controllable active motion (CAM) resistance force.
• Experimental results demonstrate high sensitivity and speed of the device.
• The PC-based feedback enables sophisticated auto-adaptable physiotherapy and extensive data recording.

Conclusions:

• The computerized CPM/CAM system offers a flexible and advanced approach to joint rehabilitation.
• The FNN control allows for precise, adaptable resistance, mimicking a damped spring.
• The system facilitates custom-designed therapy, data analysis, and remote patient monitoring.