loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Giovanni Diraco 1 ; Alessandro Leone 1 ; Pietro Siciliano 1 ; Marco Grassi 2 and Piero Malcovati 2

Affiliations: 1 CNR, Italy ; 2 University of Pavia, Italy

Keyword(s): Multi-sensor network, Ambient assisted living, Fall detection, Time-of-flight camera, Wearable accelerometer.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Home Monitoring and Assisted Living Applications ; Sensor Networks

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 multi-sensor approach for improving fall detection service in ambient assisted living contexts. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.235.176.80

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Diraco, G.; Leone, A.; Siciliano, P.; Grassi, M. and Malcovati, P. (2012). A MULTI-SENSOR SYSTEM FOR FALL DETECTION IN AMBIENT ASSISTED LIVING CONTEXTS. In Proceedings of the 1st International Conference on Sensor Networks - SENSORNETS, ISBN 978-989-8565-01-3; ISSN 2184-4380, pages 213-219. DOI: 10.5220/0003834202130219

@conference{sensornets12,
author={Giovanni Diraco. and Alessandro Leone. and Pietro Siciliano. and Marco Grassi. and Piero Malcovati.},
title={A MULTI-SENSOR SYSTEM FOR FALL DETECTION IN AMBIENT ASSISTED LIVING CONTEXTS},
booktitle={Proceedings of the 1st International Conference on Sensor Networks - SENSORNETS,},
year={2012},
pages={213-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003834202130219},
isbn={978-989-8565-01-3},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Sensor Networks - SENSORNETS,
TI - A MULTI-SENSOR SYSTEM FOR FALL DETECTION IN AMBIENT ASSISTED LIVING CONTEXTS
SN - 978-989-8565-01-3
IS - 2184-4380
AU - Diraco, G.
AU - Leone, A.
AU - Siciliano, P.
AU - Grassi, M.
AU - Malcovati, P.
PY - 2012
SP - 213
EP - 219
DO - 10.5220/0003834202130219

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic