@article{BIELSA2026104613,
title = {An analysis of gaze behavior under multisensory cognitive load in immersive environments},
journal = {Computers & Graphics},
volume = {137},
pages = {104613},
year = {2026},
issn = {0097-8493},
doi = {https://doi.org/10.1016/j.cag.2026.104613},
url = {https://www.sciencedirect.com/science/article/pii/S0097849326000841},
author = {Jaime Bielsa and Jorge Pina and Ana Serrano and Daniel Martin},
keywords = {Gaze behavior, Cognitive load, Eye tracking, Visual attention},
abstract = {Virtual Reality (VR) enables immersive and realistic experiences in which complex multisensory interactions often impose elevated cognitive demands on users. Excessive levels of cognitive load (CL) have been shown to degrade performance and user experience, motivating the search for robust and non-intrusive indicators for CL monitoring in immersive environments. While recent approaches have leveraged physiological signals for this purpose, many of these signals are sensitive to motion and require complex sensor setups. Given the widespread integration of eye tracking in modern head-mounted displays, gaze behavior emerges as a promising alternative for objective CL assessment. In this work, we present a comprehensive analysis of gaze behavior and its relationship to cognitive load in immersive, task-oriented VR. Using a publicly available dataset collected in a multisensory visual search experience, we first examine how a range of gaze-derived markers, including fixations, saccades, eye eccentricity, and pupil dilation, vary across cognitive load conditions. We then investigate their relationship with biomarkers derived from complementary physiological signals, including electrocardiogram (ECG), electrodermal activity (EDA), and respiration, to better understand how gaze-based markers relate to broader physiological responses associated with cognitive load. Our results reveal consistent changes in oculomotor behavior under high cognitive load, characterized by reduced saccade amplitudes and eye eccentricity, together with increased pupil dilation. These patterns indicate a more centered and less exploratory visual behavior, consistent with attention tunneling under high task demands. In addition, we identify strong correlations between several gaze markers and the phasic component of electrodermal activity, a well-known indicator of mental effort. Together, these findings highlight the potential of gaze-based measures as lightweight and non-intrusive indicators of cognitive load, supporting the development of adaptive, user-aware VR applications.}
}