Design and preliminary validation of a high-fidelity vascular simulator for robot-assisted manipulation.

The number of robot-assisted minimally invasive surgeries is increasing annually, together with the need for dedicated and effective training. Surgeons need to learn how to address the novel control modalities of surgical instruments and the loss of haptic feedback, which is a common feature of most surgical robots. High-fidelity physical simulation has proved to be a valid training tool, and it might help in fulfilling these learning needs. In this regard, a high-fidelity sensorized simulator of vascular structures was designed, fabricated and preliminarily validated. The main objective of the simulator is to train novices in robotic surgery to correctly perform vascular resection procedures without applying excessive strain to tissues. The vessel simulator was integrated with soft strain sensors to quantify and objectively assess manipulation skills and to provide real-time feedback to the trainee during a training session. Additionally, a portable and user-friendly training task board was produced to replicate anatomical constraints. The simulator was characterized in terms of its mechanical properties, demonstrating its realism with respect to human tissues. Its face, content and construct validity, together with its usability, were assessed by implementing a training scenario with 13 clinicians, and the results were generally positive.