Designing and evaluating safety services using depth cameras

Not receiving help in the case of an emergency is one of the most common fears of older adults that live independently at home. Falls are a particularly frequent occurrence and often the cause of serious injuries. In the last years, various ICT solutions for supporting older adults at home have been developed. Based on sensors and services in a smart environment they provide a wide range of services. In this work we have designed and evaluated safety-related services, based on a single Microsoft Kinect that is installed in a user's home. We created two services to investigate the benefits and limitations of these solutions. The first is a fall detection service that registers falls in real-time, using a novel combination of static and dynamic skeleton tracking. The second is a fall prevention service that detects potentially dangerous objects in the walking path, based on scene analysis in a depth image. We conducted technical and user evaluations for both services, in order to get feedback on the feasibility, limitations, and potential future improvements.