Texture-Driven Affective Empowerment in Bionic Machinery Installation Art: An Empirical Design Study Based on Eye Tracking and the PAD Model

Material and texture decisions in bionic machinery installation art often remain intuition-dependent, limiting the reusability of empirical evidence for experience design. Building on the biomimetic content logic in biomimetic design theory, this study proposes a targeted framework—Texture Bionics—and operationalizes texture into four quantifiable perceptual dimensions: transparency, hardness, roughness, and surface texture, forming a controllable sample space of 12 plastic texture conditions. A case database encompassing 56 representative works (2000–present) was constructed to justify material selection; plastics were chosen for their tunable properties and feasibility for parameterized modulation. In a standardized viewing setup (≈500 lx illumination; 60 cm viewing distance), participants viewed a dynamic biomimetic mechanical wing module with interchangeable textured plastic surfaces. Subjective affect responses were captured using PAD ratings, and objective attention was assessed via wearable eye-tracking technology. Repeated-measures analyses showed robust main effects of texture on total fixation duration across all four dimensions, and selective effects on time to first fixation (significant/marginal for transparency, roughness, and surface texture but not hardness); pupillary response metrics provided no stable discrimination. PAD mappings further revealed functional “role types” (e.g., Key driver, Explore guide, Stable base), and a strong association between Arousal and inter-participant variability in fixation distribution, suggesting that high-arousal textures act as strategy amplifiers rather than uniformly increasing attention. Finally, findings were translated into an actionable Texture Design Toolkit using a three-question workflow—function label → attention goal → differentiation risk—to support evidence-based orchestration of installation narratives.