This project aims to promote health monitoring in home environments and provide a more autonomous life to elderly people by watching and assisting their daily life activities. However, promoting quality aging goes far beyond the permanent analysis of vital signs, the detection, and risk of falls, the alerts for unusual routines or irregular medicines intake, as commonly addressed by today’s Ambient Assisted Living (AAL) systems. Having a quality of life in old age should mean not only a physical well-being but also a psychosocial well-being. In this context, the assessment of the state of health should also consider the emotional state. The objective of this project is to validate a more holistic approach that considers not only the medical or physical conditions but also the emotional aspects of people living in AAL sets. This project aims to study, implement and test an IoT (Internet of Things) infrastructure for monitoring the emotional state of elderly persons. Such test platform should enable multimodal data collection, to feed the necessary artificial intelligence (AI) algorithms and machine learning (ML) that will enable sensor fusion approaches for emotion classification and context adaptation.