Fall detection addresses the elderly and the disabled where accidental falls can cause severe and sometimes non-reversible injuries. A human-assisted service mobile robot is intended to monitor people in their daily activities and validate emergency scenarios such as front, back, and side falls. The service robot is deployed in a house environment and it is equipped with a Kinect sensor designated to extract a person’s skeletal model, which is used for human tracking, fall detection, and condition assessment.
This research is financially supported by the EU COALAS project. The COALAS project has been selected in the context of the INTERREG IVA France (Channel) – England European cross-border co-operation programme, which is co-financed by the ERDF.
