Automatic Fall Detection and Activity Monitoring for Elderly

Philippe Fraisse 1, * Guillaume Perolle 2 Maria Mavros 3 Igone Etxeberria 4
* Corresponding author
1 DEMAR - Artificial movement and gait restoration
CRISAM - Inria Sophia Antipolis - Méditerranée , LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Our modern societies are confronted to a new growing problem: the global ageing of population. In order to find ways to encourage elderly people to live longer in their own home, ensuring the necessary vigilance and security at the lowest cost, some tele-assistance systems are already available commercially. This article presents a specific neural network used on a portable system for classifying activities in ambulatory monitoring. After more precisions about this specific neural network, we present in the second part some experimental results from our prototype stemming from gerontologic institute Ingema.
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Journal articles
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00203386
Contributor : Philippe Fraisse <>
Submitted on : Wednesday, January 9, 2008 - 6:27:58 PM
Last modification on : Thursday, February 28, 2019 - 2:38:22 PM

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Philippe Fraisse, Guillaume Perolle, Maria Mavros, Igone Etxeberria. Automatic Fall Detection and Activity Monitoring for Elderly. Journal of eHealth Technology and Application, Tokai University - National Institute of Information and Communications Technology, 2007, 5 (3), pp.240-246. ⟨lirmm-00203386⟩

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