Color design significantly affects trust in the product and human perception. Existing color design evaluation methods rely on subjective judgment and lack continuous physical spectral grounding. In this study, we developed a sensor-based color design evaluation framework integrating hardware-level optical sensing, Commission Internationale de l’Éclairage L*a*b* color analysis, human perception evaluations, and the analytic hierarchy process. Photodiode arrays (Vishay BPW34) and an STM32F407 microcontroller unit were used to measure real-time surface spectral reflectance and illuminance to compute CIEDE2000 (ΔE00) metrics. A survey of 120 participants across seven perceptual dimensions revealed significant differences (p < 0.001), with cool tones outperforming warm tones in cleanliness and purpose. Analytic hierarchy process criteria weighting prioritized purpose (23.68%), safety (19.74%), and cleanliness (17.48%) in selecting colors. The blue–white scheme showed the highest human perception score (5.468), followed by the green–white scheme (5.124). The developed system transforms optical sensors from passive measuring tools into dynamic components for closed-loop, evidence-based healthcare product design and manufacturing quality control. Despite these results, the system needs further improvements to operate under ambient lighting fluctuations. In the following studies, it is necessary to integrate multispectral sensors and longitudinal testing data. The proposed sensor-based framework is relevant to Sustainable Development Goal 9 (SDG 9) through smart-product innovation and may support Sustainable Development Goal 12 (SDG 12) by enabling more consistent, resource-conscious color quality control; actual material savings were not measured in this study.