Performance assessment and optimization of motion planning in a surgical trainer for potential space applications

Abstract

Medical surgeries in the space environment, including long term space travel (e.g., to Mars) and permanent presence on other planetary bodies (e.g., Moon and Mars), are posing an inherent logistical, and in the absence of appropriately trained personnel (i.e., surgeons), even a potentially life-threatening challenge. As a potential mitigation the use of an existing surgical trainer tool that would allow crewmembers to acquire basic surgical skills is proposed, and to train space station personnel both in space and on the Moon and Mars to hone these skills long-term. Furthermore, this tool would potentially allow for tele-conducted surgeries, akin to the da Vinci Surgical System, controlled from Earth but executed onboard, e.g., the International Space Station. On Earth the surgical trainer can be used to train surgeons and flight surgeons. The efficiency of any surgical training system plays a significant role in its reduction of operative risks and stress associated with insufficient experience of the trainee. The primary goal of such systems is to raise the trainee to a higher level of proficiency without putting patients at risk in the operating room. The prototype for the Computer Assisted Surgical Trainer (CAST) being developed at the University of Arizona realizes an optimal motion-planning algorithm. The underlying system consists of mechanical fixtures equipped with encoders and DC motors. This hardware provides a means to accurately track the tip movements of laparoscopic instruments used in minimally invasive surgery. Furthermore it provides haptic and visual feedback to trainees by using a PID controller and augmented reality visualization. Examples of surgical guidance and the improvement of surgeon performance over time using CAST are presented.