Grant: Doctoral Award - Frederick Banting and Charles Best Canada Graduate Scholarships

We plan to develop a system that will improve the state of the art in training for laparoscopic surgery. Traditional training methods use low-fidelity models such as synthetic (rubber) skin or live animals, and are not appropriate for learning the complex skills necessary in laparoscopy. Our lab has already developed a system that allows an expert's surgical performance to be "digitally captured" using motion tracking and force sensing instruments. In this new project, we will create a system that allows this data to be "played back" to a trainee. With this system, trainees will be able to see, hear, and hapticallyfeel the expert's movements. Robotic devices will be able to move the trainee's hands through the movements that the expert previously performed, allowing them to learn subtle skills that they previously had to obtain through long sessions of trial and error. In addition, the new system will allow surgeons in rural areas to develop and practice surgical skills that they use infrequently. This system has the potential to increase surgical skill, resulting in fewer surgical complications. It also has the potential to substantially reduce the cost of surgical training, as the trainees learn faster, and the reliance on expensive animal models is decreased.