Computational Measures of Gaze Behavior Using the Concept of Situational Awareness

Eye gaze is fundamental to common sensorimotor activities. It directly indicates attention and its allocation, making it a critical human factor that reflects cognitive behavior. Data-driven measurements of gaze behavior quantitatively evaluates the allocation of visual attention, indicating the mental and physical activity status of individuals. Situational awareness provides a solid and semantically rich basis for gaze behavior during sensorimotor activities. However, few attempts have been made so far to measure eye gaze data from the perspective of situational awareness. In this paper, we propose four new computational measures of gaze behavior that align with the fundamental concept of situational awareness, effectively measuring the efficiency of visual scanning and sensorimotor activity. Our results have clearly shown that the proposed measures are effective and perform satisfactorily compared to the closely related methods. This work offers a new data-driven approach for biomarker discovery and behavioral biometrics using eye gaze data.

Publication Details

Journal
Research Portal (King's College London)
Published
2025-03-21
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
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article

Computational Measures of Gaze Behavior Using the Concept of Situational Awareness

Research Portal (King's College London)
Gaze Tracking and Assistive Technology
article

Computational Measures of Gaze Behavior Using the Concept of Situational Awareness

article en

Abstract

Eye gaze is fundamental to common sensorimotor activities. It directly indicates attention and its allocation, making it a critical human factor that reflects cognitive behavior. Data-driven measurements of gaze behavior quantitatively evaluates the allocation of visual attention, indicating the mental and physical activity status of individuals. Situational awareness provides a solid and semantically rich basis for gaze behavior during sensorimotor activities. However, few attempts have been made so far to measure eye gaze data from the perspective of situational awareness. In this paper, we propose four new computational measures of gaze behavior that align with the fundamental concept of situational awareness, effectively measuring the efficiency of visual scanning and sensorimotor activity. Our results have clearly shown that the proposed measures are effective and perform satisfactorily compared to the closely related methods. This work offers a new data-driven approach for biomarker discovery and behavioral biometrics using eye gaze data.

Research Portal (King's College London)
Reduced inequalities
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Gaze Tracking and Assistive Technology
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