Enhancing Medical Training: A Genetic Algorithm and PID Control Approach to Colonoscopy Simulations

This study introduces a simulation framework aimed at improving the training efficiency for medical residents performing colonoscopy procedures. Integrating a genetic algorithm (GA) with Proportional-Integral-Derivative (PID) control within the system provides real-time feedback on the colonoscope maneuvers across diverse patient anatomies. Traditional training methods rely on medical manikins and expert supervision, which contain limitations such as lack of immediate feedback, high costs, and scheduling complexities with medical experts. The proposed simulation addresses these gaps by automating the learning process, using GA to adapt to new patient anatomies and PID control for interactive feedback, thus enhancing learning efficiency and maneuver skill required for colonoscope. The study evaluates the system's effectiveness through experiments with various colon geometry and radius. Assessing the ability of simulation to offer precise feedback and improve maneuver strategies. Results indicate that the proposed simulation can enhance the training process, offering a tool for improving medical education.