Analyzing the Attractiveness Factors of Health Wearables for Older Adults using EGM and Quantification Theory type I

• Main Authors: Zhang, Bao-Yi, Liu, Han-Xuan, Song, Ying-Jie
• Format: Conference Proceeding
• Language: English
• Subjects: Biomedical monitoring; Evaluation Grid Method; Feature extraction; Health wearable devices; Object recognition; Older adults; Quantification theory type I; Shape; User experience; Wearable computers
• ISSN: 2251-2454
• DOI: 10.1109/ICCAR57134.2023.10151751

Through studying the appearance preferences of older adults towards health wearable monitoring devices, this study aims to design a device shape that satisfies user needs and provides a high-quality experience for older adults. Firstly, we collected and screened existing health wearable devices in the market as experimental samples. Then, we conducted user interviews and applied the evaluation grid method in Miryoku Engineering to accurately extract user-preferred design elements of wearable devices. Using the Quantification theory type I (QTT1), we analyzed the design elements of health wearable devices. Based on the user's preferences for different perceptual images of health wearable devices, we identified the attractiveness factors that affect user preferences and corresponding morphological features. By designing health wearable devices that meet user preferences, we aim to improve user compliance with the equipment and provide an enhanced user experience.