With the growing number of diabetic elderly individuals, there is an increasing need for innovative solutions to manage their condition effectively. The advent of smart wearable products, driven by the integration of wearable technology and the Internet of Things (IoT), offers promising opportunities to address these needs. However, current designs often reflect the personal style of designers rather than the specific requirements of the diabetic elderly. This paper proposes employing Kansei Engineering and the KANO Model to develop a CMF design methodology that better fits this demographic. This study conducts a questionnaire survey to quantify users’ emotional trend by finding key CMF design factors and market trends in order to research product functionality. These findings are synthesized and integrated into the design process. Experimental results demonstrate that this method enhances CMF design research for smart wearable products, optimizing practicality, aesthetics, and user experience specifically for the diabetic elderly.