• high fidelity simulation
• soft strain sensor
• training
• robot assisted thoracoscopic surgery

The number of robot-assisted minimally invasive surgeries is increasing every year, together with the request of specialized and effective training. Surgeons need to learn how to deal with new control of the surgical instruments and the loss of haptic feedback, that is a common feature of surgical robots. High fidelity physical simulation proved to be a valid training tool, and it might help in fulfilling this learning need.
This thesis work was carried out in the framework of an Intuitive technology research grant and in partnership with the robotic surgery team of Prof. Melfi (University of Pisa). The focus was on the design and realization of a high fidelity sensorized simulator of pulmonary vein and its surrounding soft tissues. The main objective is to train novices in robotic surgery to correctly perform the vein resection procedure. A portable and user-friendly training task board was designed and fabricated. The vein simulator was integrated with soft strain sensors to objectively assess the manipulation skills, as well as to provide real-time feedback to the trainee.
The simulator was characterized in terms of mechanical properties, proving its realism with respect to human tissue. A preliminary validation in terms of face, content and construct validity was positively assessed, together with the usability of the simulator in a training scenario.
The number of expert surgeons was low. Then, further tests need to be carried out to fully validate the simulator.