A Multi-Layered Adaptive Framework for Emotionally Intelligent Elderly Care Interiors

Abstract

This is a conceptual paper proposing the Multi-Layered Adaptive Framework for Emotionally Intelligent Elderly Care Interiors (MAF-EI). It addresses three fundamental limitations in current digital eldercare interior research: persistent digital exclusion among vulnerable older adults, the absence of emotionally intelligent adaptive systems, and the fragmentation of physical design, digital literacy, and social infrastructure. Drawing on systematic evidence from eighteen peer-reviewed studies (2018–2025), the framework integrates four interconnected layers: (i) Physio-Spatial Layer (biometric-responsive environmental adaptation), (ii) Cognitive-Scaffolding Layer (dynamic interface simplification based on real-time cognitive load assessment), (iii) Socio-Emotional Layer (AI-mediated community connection and intergenerational digital mentorship), and (iv) Ethical-Governance Layer (decentralized privacy-preserving data architecture). The framework is theoretically grounded in Ambient Intelligence, Embodied Cognition, and Socio-Technical Systems Theory. A three-phase mixed-methods validation protocol is designed for future empirical testing, including proposed biometric validation metrics, longitudinal well-being outcome measures, and cost-effectiveness models. The primary contribution is a paradigm shift from technology-as-tool to environment-as-partner, positioning the built environment as an active, empathetic cohabitant rather than a passive container for assistive devices.