There is a huge challenge to reach efficiency of national health systems and Information and Communication Technologies (ICTs) play a significant role towards such objective. The increasing connectivity and the fast development and availability of imaging and biometric sensors as well as of the Internet of Things devices have opened a world of possibilities. One of these examples is given by the automatic distant monitoring of Parkinson's and Alzheimer's patients by the collection of data that could be analyzed to reveal valuable insights for early detection and/or prevention of events related to their condition. In this paper, a complete overview of a system intended to improve the Quality-of-Life (QoL) of such patients is presented. The system collects signals from diverse sensors, identifies the user behavior and context, and triggers proper actions for improving the patient's QoL. The system offers comparable/improved results for the detection of abnormal behavior in daily motion with respect to the state-of-the-art.