Multi-Thread Implementation of Tool Tip Tracking for Laparoscopic Surgical Box-Trainer Intelligent Performance Assessment System

Abstract

Laparoscopic surgery has revolutionized medicine, yet it requires specific skills not traditionally taught to surgeons. Early in training, surgical trainees frequently use lowfidelity "box-trainers" to increase their skills. Evaluation of performance, however, is crude, frequently focusing on speed alone or subjective observations. There is a research collaboration between the Department of Electrical and Computer Engineering and the Department of Surgery, of the Homer Stryker M.D. Medical School, at WMU. The objective of this research is to develop an intelligent box-trainer system which incorporates sensory devices and high definition digital video cameras along with a fuzzy logic-based performance assessment system. Two of the key research problems of this work are the implementation of the tool tip tracking task and the associated performance assessment method. This system will more consistently evaluate trainees and their performance in real time without needing the presence of an independent observer. Using fuzzy logic to capture expert knowledge and fusing it with sensory data for performance assessment purposes is a new approach in the area of laparoscopic surgery training.