Fall Detection on Ambient Assisted Living using a Wireless Sensor Network

<div>In this work, a distributed system for fall detection is presented. The proposed system was designed to monitor activities of the daily living of elderly people and to inform the caregivers when a falls event occurs. This system uses a scalable wireless sensor networks to collect the data...

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Main Authors: António PEREIRA, Filipe FELISBERTO, Luis MADURO, Miguel FELGUEIRAS
Format: Article
Language:English
Published: Ediciones Universidad de Salamanca 2012-07-01
Series:Advances in Distributed Computing and Artificial Intelligence Journal
Subjects:
Online Access:https://revistas.usal.es/index.php/2255-2863/article/view/10094
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spelling doaj-87e6161bf40b41adbc56cb7fe2ecc3d92020-11-25T03:29:46ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632012-07-0111627710.14201/ADCAIJ20121162779518Fall Detection on Ambient Assisted Living using a Wireless Sensor NetworkAntónio PEREIRA0Filipe FELISBERTO1Luis MADURO2Miguel FELGUEIRAS3Polytechnic Institute of LeiriaPolytechnic Institute of LeiriaPolytechnic Institute of LeiriaPolytechnic Institute of Leiria<div>In this work, a distributed system for fall detection is presented. The proposed system was designed to monitor activities of the daily living of elderly people and to inform the caregivers when a falls event occurs. This system uses a scalable wireless sensor networks to collect the data and transmit it to a control center. Also, an intelligent algorithm is used to process the data collected by the sensor networks and calculate if an event is, or not, a fall. A statistical method is used to improve this algorithm and to reduce false positives. The system presented has the capability to learn with past events and to adapt is behavior with new information collected from the monitored elders. The results obtained show that the system has an accuracy above 98%. </div><div> </div>https://revistas.usal.es/index.php/2255-2863/article/view/10094ambient assisted livingelderlyfall detectionlogistic regressionwireless sensor networks
collection DOAJ
language English
format Article
sources DOAJ
author António PEREIRA
Filipe FELISBERTO
Luis MADURO
Miguel FELGUEIRAS
spellingShingle António PEREIRA
Filipe FELISBERTO
Luis MADURO
Miguel FELGUEIRAS
Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
Advances in Distributed Computing and Artificial Intelligence Journal
ambient assisted living
elderly
fall detection
logistic regression
wireless sensor networks
author_facet António PEREIRA
Filipe FELISBERTO
Luis MADURO
Miguel FELGUEIRAS
author_sort António PEREIRA
title Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
title_short Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
title_full Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
title_fullStr Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
title_full_unstemmed Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
title_sort fall detection on ambient assisted living using a wireless sensor network
publisher Ediciones Universidad de Salamanca
series Advances in Distributed Computing and Artificial Intelligence Journal
issn 2255-2863
publishDate 2012-07-01
description <div>In this work, a distributed system for fall detection is presented. The proposed system was designed to monitor activities of the daily living of elderly people and to inform the caregivers when a falls event occurs. This system uses a scalable wireless sensor networks to collect the data and transmit it to a control center. Also, an intelligent algorithm is used to process the data collected by the sensor networks and calculate if an event is, or not, a fall. A statistical method is used to improve this algorithm and to reduce false positives. The system presented has the capability to learn with past events and to adapt is behavior with new information collected from the monitored elders. The results obtained show that the system has an accuracy above 98%. </div><div> </div>
topic ambient assisted living
elderly
fall detection
logistic regression
wireless sensor networks
url https://revistas.usal.es/index.php/2255-2863/article/view/10094
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AT filipefelisberto falldetectiononambientassistedlivingusingawirelesssensornetwork
AT luismaduro falldetectiononambientassistedlivingusingawirelesssensornetwork
AT miguelfelgueiras falldetectiononambientassistedlivingusingawirelesssensornetwork
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