People with stroke are among the most relevant target groups for unobtrusive monitoring. Worldwide, stroke is the second most frequent cause for lasting disability and causes a substantial burden for the individual, caregivers and society. Thanks to improved treatment, many stroke survivors can be discharged to their homes. However, many have to live with disabilities and are prone to declining function, cognitive impairment and depression. With the acquired data, we want to create a database where digital behavior is analyzed with advanced computational methods. In collaboration with the Department of Cognitive Psychology, University of Leiden, Netherlands, these data will be used to discover specific features for different health issues and to develop tools for the early detection of functional decline for different populations.