Abstract

The aging population represents an emerging challenge for healthcare since elderly people frequently suffer from chronic diseases requiring continuous medical care and monitoring. Sensor networks are possible enabling technologies for ambient assisted living solutions helping elderly people to be independent and to feel more secure. This paper presents a multi-sensor system for the detection of people falls in home environment. Two kinds of sensors are used: a wearable wireless accelerometer with onboard fall detection algorithms and a time-of-flight camera. A coordinator node receives data from the two sub-sensory systems with their associated level of confidence and, on the basis of a data fusion logic, it operates the validation and correlation among the two sub-systems delivered data in order to rise overall system performance with respect to each single sensor sub-system. Achieved results show the effectiveness of the suggested multisensor approach for improving fall detection service in ambient assisted living contexts.

Autore Pugliese

• Leone Alessandro , Diraco Giovanni , Siciliano Pietro Aleardo

Tutti gli autori

• Diraco G.; Leone A.; Siciliano P.; Grassi M.; Malcovati P.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2012

ISSN

Non Disponibile

ISBN

9789898565013

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

Non Disponibile