A Novel Low Cost Robot for Skill Training in Minimally Invasive Surgery

In this paper, a novel simple robotic system is developed for surgical training in minimally invasive surgery (MIS). The robot automatically measures motion data of instruments in real time using internal encoders, without additional sensing mechanisms. Kinematics equations are integrated in the control software to map motor motion to the instrument tip motion. These recorded motion data then can be analyzed in the computer system for objective evaluation using well established criteria. A neural network algorithm is employed in real time as the observer of weight and inertia effects which are compensated through motor control. Experiment results show that this compact robot provides good stability and smooth motion while guiding instruments using surgeon input. The tracking resolution is sufficient for objective evaluation purposes. The robot combines the realistic feel of MIS instruments with the capability of the computer to tabulate objective measures of performance and skill. Its flexibility as a training instrument can be of great benefit in both providing surgeons with much-needed practice and assessing the outcomes of that practice.