AI-Enabled Home Healthcare

This academic review examines the evolution of AI-enabled home healthcare technologies, focusing on how medical wearables and digital diagnostics can improve chronic disease management. While these tools offer sophisticated data tracking, the authors identify significant barriers to long-term adoption, such as complex onboarding, user fatigue, and physical discomfort. To address these challenges, the text introduces the Pi-CON methodology, a framework advocating for systems that are passive, non-contact, and continuous. By shifting toward unobtrusive ambient sensing—like radar or camera-based monitoring—healthcare can move away from demanding user interactions. The source ultimately suggests that the future of smart health relies on invisible, integrated technology that prioritises user ease and data privacy. This approach ensures that medical monitoring becomes a seamless part of daily life rather than a burdensome task.