Cognitive effort detection for tele-robotic surgery via personalized pupil response modeling

Regine Büter, Roger D. Soberanis-Mukul, Rohit Shankar, Paola Ruiz Puentes, Ahmed Ghazi, Jie Ying Wu, Mathias Unberath

Abstract: Gaze tracking and pupillometry are established proxies for cognitive load, giving insights into a user’s mental effort. In tele-robotic surgery, knowing a user’s cognitive load can inspire novel human–machine interaction designs, fostering contextual surgical assistance systems and personalized training programs. While pupillometry-based methods for estimating cognitive effort have been proposed, their application in surgery is limited by the pupil’s sensitivity to brightness changes, which can mask pupil’s response to cognitive load. Thus, methods considering pupil and brightness conditions are essential for detecting cognitive effort in unconstrained scenarios.