Claus Backhaus, FH Münster, Steinfurt, Deutschland, claus.backhaus@fh-muenster.de Uvo Hölscher, FH Münster, Steinfurt, Deutschland, hoelscher@fh-muenster.de Older people are prone to fall due to their reduced mobility, effects of medication and decreased brawn. Despite of the fact that not all falls lead to injuries, its percentage is high enough to be considered as a major publichealth concern. This gains even more pertinence by taking into account that, based on the fear of falling, avoidance of movement reduces social interactions. Several approaches were made to detect falls focused on analysing body movements and identifying changes in acceleration. Unfortunately, these systems are compromised when the fall-speed is not high enough or the impact to the ground is smoothed in some manner. The developed system intends to solve these issues by monitoring not only the body movements but also the body position, obtaining a method to detect fast and slow falls. Position is calculated using high resolution barometric pressure sensors to compute the height difference between the chest and the feet. Motion sensors capture also the movements on these points, enabling to distinguish falls in contrast to daily life activities with similar body positions. Additionally, our system involves relatives and neighbours offering a new way of emergency response. Whenever a fall occurs, the system begins to communicate with the user in order to check how severe the injury is. Depending on the user reply, the system decides to call emergency medical assistance or to use a neighbour and family network to provide help for minor injuries. Therefore, we are capable of offering a fast aid attention, reducing unnecessary calls to emergency services and providing a self-determined life for older people with ongoing participation in their social environment. The presented contribution shows the developed system in detail and gives an overview about our first evaluation results.