Fall incidents and the sustained injuries represent the main causes of accidents for elderly people, and also the third cause of chronic disability. The rapid detection of a fall event can reduce the mortality risk, avoiding also the aggravation of injuries. In this paper an embedded healthcare system based on a microwave radar is presented. A Continuous Wave (CW) Doppler radar is used to detect the changes in speed of different persons experienced during daily activities, namely falling and normal/random movements. The resulted speed signals are then processed in real-time by a digital signal processor (DSP) in order to detect fall incidents. Experimental results, conducted on real human volunteers in a real room.

Healthcare System for Non-Invasive Fall Detection in Indoor Environment / Mercuri, M; Garripoli, C; Karsmakers, P; Soh, P. J.; Vandenbosch, G. A. E.; Pace, Calogero; Leroux, P; Schreurs, D.. - 351:(2015), pp. 145-152. (Intervento presentato al convegno APPLEPIES 2014 - Applications in Electronics Pervading Industry, Environment & Society tenutosi a Roma nel 5-6 Maggio 2014) [10.1007/978-3-319-20227-3_19].

Healthcare System for Non-Invasive Fall Detection in Indoor Environment

Mercuri M
;
2015-01-01

Abstract

Fall incidents and the sustained injuries represent the main causes of accidents for elderly people, and also the third cause of chronic disability. The rapid detection of a fall event can reduce the mortality risk, avoiding also the aggravation of injuries. In this paper an embedded healthcare system based on a microwave radar is presented. A Continuous Wave (CW) Doppler radar is used to detect the changes in speed of different persons experienced during daily activities, namely falling and normal/random movements. The resulted speed signals are then processed in real-time by a digital signal processor (DSP) in order to detect fall incidents. Experimental results, conducted on real human volunteers in a real room.
2015
978-3-319-20227-3
Fall detection
Health monitoring
LS-SVM
Movement classification
Radar remote sensing
Telehealth systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/150307
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