Technology acceptance and perceived safety in AI-driven home monitoring for mild cognitive impairment

Digital health technologies and AI-driven home monitoring systems are increasingly deployed to support individuals with Mild Cognitive Impairment or cognitive decline, offering opportunities for early detection, continuous assessment, and enhanced safety. While prior research has predominantly focused on technical performance and data accuracy, less attention has been dedicated to patients' lived experiences. This study adopts a qualitative approach to explore the experiences of patients participating in the SERENADE project. Seventeen patients and seven caregivers engaged in semi-structured interviews after one year of adoption of smart home monitoring technologies. Codebook thematic analysis revealed that cognitive decline shaped participants' perceptions of monitoring technologies, with some reporting reassurance and enhanced control, while others experienced frustration when system features conflicted with daily routines or autonomy. Technology acceptance was influenced by effort expectancy, performance expectancy, facilitating conditions, social influence and participants' relationship with monitoring tools. Findings advance current understanding of perceived safety in home-based digital care, demonstrating that it extends beyond technical reliability. These insights inform the design of adaptive, user-centered monitoring systems that enhance perceived safety and support autonomy, reassurance, and continuity of care in cognitively vulnerable populations.