A Surgeon’s Operating Skills-Based Non-Interference Operation Detection Method for Novel Vascular Interventional Surgery Robot Systems

Abstract

The vascular interventional surgery (VIS) is the most popular treatment for the cardiovascular and cerebrovascular diseases. Master-slave VIS robot is a promising technology to further improve the operation accuracy and surgical safety of both the patient and surgeon. The surgical outcome of robot assisted VIS highly depends on surgeon’s operating skills. However, current VIS robot systems affect the exerting of surgeon’s operating skills with different degrees due to the master manipulators with rigid-link structure or low detecting accuracy. To address this issue, a novel vascular interventional surgery robot based on surgeon’s operating skills is developed in this paper. A master manipulator is developed to contactlessly measure the surgeon’s operating motion. The surgeon operates the catheter with no limit, just as the operating manner in conventional VIS. It is enabled by measuring the catheter’s axial motion through tracking the edge of a series of markers with a macro camera, and by measuring the catheter’s rotational motion via a high-precise MEMS (Micro-Electro-Mechanic-System) gyroscope. Then, the developed master manipulator is integrated with a slave robot to construct the master-slave VIS robot system. Experimental results show that the detecting accuracy of the developed master manipulator are 0.71° and 0.104mm. Experimental results of surgical tasks implemented in EVE (endovascular evaluator) indicate that the developed robot system is superior to the system using a phantom as the master manipulator according to the metrics including operating time, path length, maximum speed and maximum accelerate.