Image-based object state modeling of a transfer task in simulated surgical training
Kuo Shiuan Peng, Minsik Hong, Jerzy W. Rozenblit · 2017
This paper proposes a real-time, image-based training scenario comprehension method. This method aims to support the visual and haptic guidance system for laparoscopic surgery skill training. The target task of the proposed approach is a simulation model of a peg transfer task, which is one of the hands-on exam topics in the Fundamentals of Laparoscopic Surgery certification. In this paper, a simulation process of an image-based object state modeling method is proposed. It generates a system object state of the transfer task to support the guidance system. A rule-based, intelligent system is used to discern the object state without the aid of any object template or model. This is the novelty of the proposed method.