Healthy Aging through Pervasive Predictive Analytics for Prevention and Rehabilitation of Chronic Conditions

The current aging of the population is linked to many societal challenges, especially in healthcare. Co-morbid chronic conditions are prevalent in older age and drastically affect people's wellbeing, but they are difficult to study due to the many health determinants involved. For this reason, we propose a multidisciplinary ICT-based approach for the prevention and rehabilitation of chronic conditions using unobtrusive and pervasive sensors, interactive activities, and predictive analytics. This framework allows fine monitoring of older people's health and improved personalized care for healthy aging. To illustrate the advantages of this pervasive and data-driven approach we set forth a conceptual model, in which we use cardiovascular disease, Alzheimer's disease, depression and falls as examples of common co-morbid conditions in older people.