Research on Age-Friendly Interaction Design of Smart Wearable Health Watches Integrating FMEA and RCA

Aging populations in China face growing challenges adapting to digital and intelligent healthcare advances due to technological, cultural, and personal limitations. The main goal of this study was to explore interaction design methods through systematic experiments and design practices to facilitate upgrades of aging-friendly smart wearable watches and enhance user experience. Semi-structured interviews were conducted with 22 elderly people to obtain the pain points and needs and to design a preliminary interaction interface prototype accordingly. Combining Hierarchical Task Analysis (HTA) and Systematic Human Error Reduction and Prediction Approach (SHERPA), 17 error steps were captured and categorized into 5 error types. Failure Mode and Effects Analysis (FMEA) is applied to identify failure modes in the prototype design, calculate the Risk Priority Number (RPN), and analyze the causes from users, system, environment, and tasks through Root Cause Analysis (RCA). Subsequently, the design is improved and FMEA is conducted again to verify the effectiveness. The P-value of the paired sample t-test of the two RPNs (p=0.000<0.050) indicates that the interaction design guided by the above methods can effectively identify and solve the problems, and enhance the user experience of the elderly.