Emotion-Driven Intelligent Product Design Based on Deep Learning

This research investigates the integrated application of deep learning technologies in the field of emotion-driven interior soft decoration product design. Through comprehensive online surveys conducted with over 1000 participants and coupled with biometric feedback from 300 individuals, this study offers a multi-faceted analysis of user emotions during interactions with interior soft decoration products. The employment of a finely-tuned Convolutional Neural Network (CNN) model facilitated the extraction of key emotional design elements, indicating that around 520 of the surveyed participants were satisfied with certain interior soft decoration designs, while a minority of 80 expressed dissatisfaction. Moreover, the biometric data revealed a significant correlation between increased heart rates (exceeding 85 beats per minute) and intense emotional responses. The integration of biometric and questionnaire textual data suggested that users indeed experienced strong positive emotions in interactions with specific soft decoration products. The study also addresses potential challenges, including possible biases in data collection and the inherent limitations of deep learning models. The findings underscore the significant potential of deep learning in capturing the complex patterns of user emotions, providing valuable insights for the future design of emotion-centric interior soft decoration products. Through this interdisciplinary approach, the study charts a promising direction for the advancement of artistic disciplines such as interior design and soft decoration product design, emphasizing the importance of understanding and incorporating user emotion in the design process.