Design of Affect-aware Systems for the Study of Well-Being

Current demographic evidence indicates that contemporary Europeans live longer than ever before. This does not necessarily mean they live healthier and in fact there is a direct relationship between aging and disability, such that as the population gets older, the number of people with disability increases. This means that the elderly will represent the largest group of people with disabilities in the coming years. Thus, perhaps just as important as life expectancy is the quality of life of elderly people since it is this element that most affects individuals as well as their families and friends. In this paper we propose the combination of smart environments and affective wearables to support physical and mental well-being. We show experimental results that demonstrate that it is possible to perform assessment similar to the one provided by the Daily Reconstruction Method (DRM), a popular questionnaire-based instrument to estimate well-being, without the need of repeated human intervention. Main content. We describe the concept of affect-aware well-being monitoring which integrates elements of context-aware behaviour modelling and psyschophysiology to offer unobtrusive, continuous insight into emotional elements of daily life that influence well-being in the lives of elderly people. We use this approach to outline an automated implementation of the DRM. Results. Results from experimental sessions carried out in a Smart home called the iSpace involving a male person wearing an affective wearable called the XVest, demonstrated a higher number of valenced-emotional changes as the day progressed which was related to the activity of the person. Conclusion. We show that it is feasible to assess the core emotional elements of well-being in ways that do not require the use of questionnaires and enable continuous, unobtrusive analysis with little disturbance of daily life activities. This is achieved by the inclusion of emotional information into the control and decision mechanism of pervasive systems.