An unobtrusive method to realize human fall detection by using bluetooth beacons, a smartphone and a low cost mobile robot is presented. The method is composed by five steps. The first consists in extracting features from the smartphone acceleration data, which are then analysed online by the fall detection algorithm. Once the fall event is detected, then the location is determined by using the bluetooth signal received from beacons. Then, the mobile robot moves towards the user's location, and finally verifies if the detected fall event is a true positive or not, through a procedure based on voice interaction with the potentially fallen user. The method has been tested in laboratory, proving to be a viable solution to perform fall detection in smart homes via consumer devices.
Real-time fall detection system by using mobile robots in smart homes / Ciabattoni, L.; Ferracuti, F.; Foresi, G.; Freddi, A.; Monteriu, A.; Pagnotta, D. Proietti. - ELETTRONICO. - (2017), pp. 15-16. (Intervento presentato al convegno IEEE 7th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) tenutosi a Berlin, Germany nel Sept. 3-6 , 2017) [10.1109/ICCE-Berlin.2017.8210576].
Real-time fall detection system by using mobile robots in smart homes
Ciabattoni, L.;Ferracuti, F.;Foresi, G.;Freddi, A.;Monteriu, A.;Pagnotta, D. Proietti
2017-01-01
Abstract
An unobtrusive method to realize human fall detection by using bluetooth beacons, a smartphone and a low cost mobile robot is presented. The method is composed by five steps. The first consists in extracting features from the smartphone acceleration data, which are then analysed online by the fall detection algorithm. Once the fall event is detected, then the location is determined by using the bluetooth signal received from beacons. Then, the mobile robot moves towards the user's location, and finally verifies if the detected fall event is a true positive or not, through a procedure based on voice interaction with the potentially fallen user. The method has been tested in laboratory, proving to be a viable solution to perform fall detection in smart homes via consumer devices.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
