Beyond Gaze: Quantifying Conscious Perception Through an Innovative Eye Tracking Biomarker

This paper introduces a novel digital biomarker based on eye tracking data, the Conscious Perception Index (CPI), designed to measure conscious perception by leveraging established eye gaze metrics. The CPI builds upon foundational eye-tracking markers, including saccades and fixation statistics, coefficient K, and cognitive load, to provide a continuous, quantified computation of perceptual awareness in real time. To evaluate CPI's effectiveness, a change blindness study was conducted in a VR setting, allowing the analysis of conscious perception within an explicit interaction context. Findings demonstrate that the CPI provides a reliable measure of conscious engagement, with significant results in statistical analysis supporting its robustness. Classification via LogisticRegression is able to separate conscious interaction from observational behavior with an accuracy of 83.3%. This research underscores CPI's potential to enhance eye-tracking applications in cognitive science and human-computer interaction, opening new avenues for measuring perceptual awareness and refining interactive technologies based on user perception.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-05-22
DOI
https://doi.org/10.1145/3725831
Primary Topic
Visual Attention and Saliency Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Beyond Gaze: Quantifying Conscious Perception Through an Innovative Eye Tracking Biomarker

Philipp Raggam, Benedikt Gollan
Proceedings of the ACM on Human-Computer Interaction
Visual Attention and Saliency Detection
article

Beyond Gaze: Quantifying Conscious Perception Through an Innovative Eye Tracking Biomarker

Philipp Raggam, Benedikt Gollan
article en

Abstract

This paper introduces a novel digital biomarker based on eye tracking data, the Conscious Perception Index (CPI), designed to measure conscious perception by leveraging established eye gaze metrics. The CPI builds upon foundational eye-tracking markers, including saccades and fixation statistics, coefficient K, and cognitive load, to provide a continuous, quantified computation of perceptual awareness in real time. To evaluate CPI's effectiveness, a change blindness study was conducted in a VR setting, allowing the analysis of conscious perception within an explicit interaction context. Findings demonstrate that the CPI provides a reliable measure of conscious engagement, with significant results in statistical analysis supporting its robustness. Classification via LogisticRegression is able to separate conscious interaction from observational behavior with an accuracy of 83.3%. This research underscores CPI's potential to enhance eye-tracking applications in cognitive science and human-computer interaction, opening new avenues for measuring perceptual awareness and refining interactive technologies based on user perception.

Proceedings of the ACM on Human-Computer InteractionVol. 9(3)
Openalex Percentile: Top 91%
Visual Attention and Saliency Detection
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