Research on Visually Adaptive Interface Color of Intelligent Guidance Based on Group’s Behavior-Emotion Consensus

To explore the differentiated color design requirements of users with varying visual acuity in intelligent guidance interfaces, we employed an interactive genetic algorithm integrating the behavior-emotion consensus model to analyze users’ preferences for hue, saturation, and brightness. The results reveal distinct patterns: low-diopter users prefer cool hues, high-diopter users prefer warm hues, whereas normal-diopter users prefer neutral hues. Moreover, the severity of refractive error is generally positively correlated with the degree of saturation and brightness of the users’ preferred interface information. Crucially, navigation icons dominate users’ preferences, with their subordinate reminder content adopting similar but weaker color attributes, while selection icons require distinct color performance to support the rapid positioning and accurate interaction. Finally, we developed an adaptive color design framework from the human-computer-environment perspective, aiming to optimize service efficiency, extend usability across diverse user groups, and accommodate personalized needs, aligning with the human-centered objectives of this public service.