Attention-Driven Rendering and Interface Adaptation Using Eye-Tracking Data
DOI:
https://doi.org/10.46243/jst.2026.v11.i02.pp01-15Keywords:
Human–Computer Interaction (HCI), Eye-Tracking, Computational Attention, Adaptive Interfaces, Visual Attention, Luxury Digital InterfacesAbstract
This study investigates computational attention mechanisms in digital luxury interfaces using eye-tracking and predictive modeling. Across three experiments (N = 60), ocular biometric measures, including fixation duration, saccadic frequency, and fixation density, were analyzed during exposure to high-fidelity fashion stimuli containing aesthetic and brand-specific elements. Results showed that aesthetic fixations were the strongest predictors of brand attention, accounting for 40.3% of variance in brand engagement, while materialism dimensions selectively influenced attention toward symbolic status cues
The findings support a gaze-driven Human–Computer Interaction (HCI) framework in which aesthetic salience functions as a primary attentional signal within visually dense digital environments. From a systems-design perspective, the study proposes an attention-adaptive interface model integrating real-time ocular metrics into rendering and layout optimization processes. The research contributes a computational framework linking biometric attention sensing with adaptive interface engineering for mobile commerce, social media, and immersive digital environments.
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