Cognitive skills assessment during robot-assisted surgery: separating the wheat from the chaff

Abstract

Objective: To investigate the utility of cognitive assessment during robot-assisted surgery (RAS) to define skills in terms of cognitive engagement, mental workload, and mental state; while objectively differentiating between novice and expert surgeons.

Subjects and methods: In all, 10 surgeons with varying operative experience were assigned to beginner (BG), combined competent and proficient (CPG), and expert (EG) groups based on the Dreyfus model. The participants performed tasks for basic, intermediate and advanced skills on the da Vinci Surgical System. Participant performance was assessed using both tool-based and cognitive metrics.

Results: Tool-based metrics showed significant differences between the BG vs CPG and the BG vs EG, in basic skills. While performing intermediate skills, there were significant differences only on the instrument-to-instrument collisions between the BG vs CPG (2.0 vs 0.2, P = 0.028), and the BG vs EG (2.0 vs 0.1, P = 0.018). There were no significant differences between the CPG and EG for both basic and intermediate skills. However, using cognitive metrics, there were significant differences between all groups for the basic and intermediate skills. In advanced skills, there were no significant differences between the CPG and the EG except time (1116 vs 599.6 s), using tool-based metrics. However, cognitive metrics revealed significant differences between both groups.

Conclusion: Cognitive assessment of surgeons may aid in defining levels of expertise performing complex surgical tasks once competence is achieved. Cognitive assessment may be used as an adjunct to the traditional methods for skill assessment during RAS.

Keywords: EEG; brain-computer interface; cognitive assessment; expertise; robot-assisted surgery.