Abstract
Introduction: Surgeons’ cognitive workload should be controlled during a surgical intervention for a successful and safe performance. Eye tracking technologies could be used for cognitive workload monitoring by analyzing the pupil size and blink frequency of surgeons. This work aims to study the surgeons’ cognitive workload watching an advanced laparoscopic video. Methods: 16 surgeons (5 experts, 11 novices) participated in the study watching a colectomy video consisting of eight steps with introductory titles. Surgeons’ gaze was recorded with eye tracking glasses while visualizing the video, from which pupil size and blink frequency were analyzed. Results: Pupil diameter of surgeons increased during the visualization of steps and decreased during the titles. Two specific steps of the intervention produced the highest pupil diameter of surgeons. When the pupil diameter increased the blink frequency decreased. Pupil diameter tended to decrease as the video is watched, which is mainly due to expert surgeons, who had a lower pupil diameter than novices. Conclusions: Eye tracking technologies allow monitoring the cognitive workload of surgeons in surgical procedures. Larger pupil size and shorter blink frequency means greater cognitive workload. Such metrics could be used to objectively label the difficult tasks within the surgical procedure. Surgical videos used for training of surgeons should be short, according to micro-learning, since cognitive workload decreases over time while visualizing them. Based on proposed metrics, eye tracking technologies could be used to distinguish the level of experience of surgeons, since cognitive workload is sensitive to the skill level of surgeons.
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Ortega-Morán, J.F., Pagador, J.B., Luis-del-Campo, V., Gómez-Blanco, J.C., Sánchez-Margallo, F.M. (2020). Using Eye Tracking to Analyze Surgeons’ Cognitive Workload During an Advanced Laparoscopic Procedure. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_1
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