Predicting Laparoscopic Surgical Skills of Trainees with Eye Metrics Associated with Focused Attention and Workload. (September 2022)

• Record Type: Journal Article
• Authors: Deng, Shiyu; Wang, Tianzi; Hartman-Kenzler, Jacob; Henrickson Parker, Sarah; Safford, Shawn D.; Barnes, Laura E.; Lau, Nathan
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 66:Part 1(2022)
• Page Start: 216
• Page End: 220
• Publication Date: 2022-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181322661156
• Languages: English
• ISSNs: 1541-9312

Abstract

Eye metrics are effective indicators of focused visual attention and perceived workload that have been used to differentiate surgical expertise and task difficulties. However, the change in eye metrics throughout surgical training in a cohort of trainees is under-investigated. This study collected eye-tracking data from 13 medical students practicing the peg transfer task until reaching the passing criteria of the Fundamentals of Laparoscopic Surgery. Six eye metrics measuring focused visual attention and workload were computed and then used in multiple linear regression analysis to predict trial completion time. All predictors were significant in the regression model, collectively explaining 61.7% of the variance in log-transformed completion time. Fixation rates and gaze entropy were the most important metrics at revealing skill acquisition as medical students self-train on the peg-transfer task. The results on these eye metrics demonstrate potential in assessing surgeons-in-training and providing feedback to ensure surgical competency.