Development of a Robotic Catheter Manipulation System Based on BP Neural Network PID Controller

Area of Science:

• Robotics
• Medical Engineering
• Control Systems

Background:

• Artificial interventional therapy often involves manual catheter operations with limited precision.
• Surgeons performing these procedures face significant radiation exposure risks.
• Existing control systems may lack the flexibility and rapidity needed for complex remote surgeries.

Purpose of the Study:

• To develop a robotic catheter operating system for remote surgical assistance.
• To mitigate radiation exposure for surgeons during interventional procedures.
• To enhance the precision and control of catheter manipulation in remote operations.

Main Methods:

• Implementation of a novel surgical robot system for catheter control.
• Integration of a Backpropagation (BP) neural network with a Proportional-Integral-Derivative (PID) controller.
• Comparative analysis of the BP neural network PID controller against traditional PID controllers.

Main Results:

• The BP neural network PID controller demonstrated feasible and effective performance in remote catheter operations.
• The new control algorithm significantly improved synchronization accuracy compared to traditional PID controllers.
• The system showed enhanced flexibility and rapidity in achieving desired control parameters.

Conclusions:

• The developed robotic system effectively assists surgeons in remote catheter operations.
• The BP neural network PID controller offers superior synchronization performance for enhanced surgical precision.
• This approach successfully reduces surgeon radiation exposure in interventional therapy.