Eye-movement entropy: Indicator construction, method implementation, and multidomain applications

Abstract: Eye-movement entropy is an information-theoretic measure of eye movement behavior. It complements conventional eye-tracking measures by quantifying the complexity and uncertainty of visual scanning based on the spatial distribution of fixations and the transitions between successive fixations. Gaze entropy characterizes how fixations are distributed across space, whereas visual attention entropy quantifies uncertainty in the allocation of visual attention. Researchers have used eye-movement entropy to investigate visual search, attentional allocation, and individual differences, and to assess cognitive states, task performance, and physical and mental health. Future research should standardize the calculation and reporting of eye-movement entropy to improve the robustness and comparability of findings across studies. Developing dynamic models and expanding the range of entropy measures would allow researchers to characterize a broader set of scanning patterns. Evaluating the reliability and validity of these measures across tasks and settings will help establish when they can be used in research and practice.