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This paper presents a hardware and software framework for reliable fall detection in the home environment, with particular focus on the protection and assistance to the elderly. The integrated prototype includes three di®erent sensors: a 3D Time-Of-Flight range camera, a wearable MEMS accelerometer and a microphone. These devices are connected with custom interface circuits to a central PC that collects and processes the information with a multi-threading approach. For each of the three sensors, an optimized algorithm for fall-detection has been developed and benchmarked on a collected mulitimodal database. This work is expected to lead to a multi-sensory approach employing appropriate fusion techniques aiming to improve system precision and recall.
Publication date: 
1 Oct 2008

Allesandro Leone, Giovanni Diraco, Cosimo Distante, Pietro Siciliano, Mattia Malfatti, L Gonzo, M Grassi, A Lombardi, G Rescio, P Malcovati, V Libal, J Huang, G Potamianos

Biblio References: 
Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications-M2SFA2 2008