This paper describes the development and testing of an Ambient Assisted Living (AAL) solution that combines state-of-the- art sensor technology with a social network application to empower elders to stay active, autonomous and socially connected and consequently support and unburden family caregivers. From a very early development phase both social scientists and engineers worked together to ensure a holistic approach to the development of the technology. To get a better insight into the needs, wishes and requirements of potential user groups, a qualitative approach was used to collect data among elderly and their caregivers from three European countries, namely Belgium, France and the United Kingdom. For the development of the technology, very low-resolution (900-pixel) visual sensors and Passive InfraRed (PIR) sensors were used and installed in a couple of homes of elderly to enable the monitoring and the analysis of the in-home activities of the elderly. In our application, automated analysis of both in-home activities and social network activities are fused to recommend new social connections and personalized activities to the elderly in order to stimulate social and physical activity. Additionally, algorithms for behavioral change analysis on the sensor data follow the health status of the elderly, such as the detection of disturbed sleep and eat patterns. From the qualitative studies interesting findings arose such as elderly mentioning safety and mobility benefits and the increased peace of mind while privacy issues, the lack of human touch and an unfelt need for support formed potential barriers towards adoption of AAL technologies.
|Publication status||Published - Apr 2016|