Toward a Non-Intrusive, Affordable Platform for Elderly Assistance and Health Monitoring

Abstract

Ambient Assisted Living (AAL) in general and Activity Recognition (AR) in particular are active fields of research that aim at assisting people in their Activities of Daily Living (ADL). In recent years, we have seen an increased interest in their applicability to the rural seniors who are slowly losing their autonomy due to aging and chronic diseases. One research venue is to aggregate and seek for correlations between the physiological data that serves to monitor the health of the elderly, their ADLs, their movements and any other data that may be collected about their immediate environment. In this paper, we are tackling the possibility of developing a non-intrusive and affordable system based on embedded health, movement, activity and location sensors. Furthermore, we discuss the main concepts behind the creation of a layered, flexible and highly modular architecture that focuses on how the integration of newly combined sensor data can be achieved. Using a mobile phone application prototype, our work has shown that we can integrate two non-invasive technologies that are not necessarily the newest, but the most affordable, scalable and ready to be deployed in real life settings.