Objective Assessment of Laparoscopic Skills Using Fitts’ Law in Virtual Reality Simulations

Abstract

This study proposes using Fitts’ Law metrics to objectively assess laparoscopic skills, specifically the adaptation to the inverted laparoscopic tool motion. A multi-tapping Fitts’ law task is designed for a custom-developed laparoscopic virtual reality haptic training simulator. The task has two experimental conditions: with and without inverted visual tool movements, performed by two groups of twenty-four novices. The Mann–Whitney–Wilcoxon analysis indicated a significant difference in movement time (p < 0.001) between inversion and non-inversion conditions. Inverted motion takes 11.86% longer with lower throughput (2.573 bits/sec) compared to the non-inversion (3.133 bits/sec). Movement offset and variability along the y and z axes are significantly larger (p < 0.05) during inversion than in non-inversion. The findings demonstrate that Fitts’ law metrics are correlated with laparoscopic tool inversion. Additional research with surgeons of diverse skill levels will facilitate applying Fitts’ law as a standardized method for laparoscopic assessment.