A User-Centered Framework for Smart Glasses Design: Integrating KANO–AHP–FCE and AIGC for Applied Wearable Interface Design

This study addresses the design challenges of daily-use smart glasses by proposing a user-centered design and evaluation framework that integrates the KANO model, the Analytic Hierarchy Process (AHP), Fuzzy Comprehensive Evaluation (FCE), and Artificial Intelligence Generated Content (AIGC)-assisted concept generation. User requirements were identified through interviews with 20 participants and user journey map analysis, classified using a KANO questionnaire survey with 309 valid responses, weighted through AHP, and used to guide AI-assisted visual generation based on Low-Rank Adaptation (LoRA) fine-tuning and a ComfyUI workflow. The results show that Functionality and Performance had the highest criterion weight, while multi-scenario mode switching, misoperation recovery, and lightweight structural design were identified as the most critical design attributes. Three design schemes, including a commercial reference product, a conventional 3D-rendered non-AIGC concept, and the proposed AIGC-assisted scheme, were evaluated using FCE. The AIGC-assisted scheme achieved the highest comprehensive score. The study demonstrates that combining quantitative requirement modeling with generative design can support a systematic workflow from user demand identification to design scheme evaluation. The proposed framework provides a practical reference for smart wearable product design and may also inform wearable interface applications in digital cultural heritage and museum interpretation contexts.