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Real Time Recognition of Elderly Daily Activity using Fuzzy Logic through Fusion of Motion and Location Data

by Shadi Khawandi, Bassam Daya, Pierre Chauvet
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 3
Year of Publication: 2012
Authors: Shadi Khawandi, Bassam Daya, Pierre Chauvet
10.5120/8549-2109

Shadi Khawandi, Bassam Daya, Pierre Chauvet . Real Time Recognition of Elderly Daily Activity using Fuzzy Logic through Fusion of Motion and Location Data. International Journal of Computer Applications. 54, 3 ( September 2012), 55-60. DOI=10.5120/8549-2109

@article{ 10.5120/8549-2109,
author = { Shadi Khawandi, Bassam Daya, Pierre Chauvet },
title = { Real Time Recognition of Elderly Daily Activity using Fuzzy Logic through Fusion of Motion and Location Data },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 3 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 55-60 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number3/8549-2109/ },
doi = { 10.5120/8549-2109 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:46.992428+05:30
%A Shadi Khawandi
%A Bassam Daya
%A Pierre Chauvet
%T Real Time Recognition of Elderly Daily Activity using Fuzzy Logic through Fusion of Motion and Location Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 3
%P 55-60
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the major problems that may encounter old people at home is falling. Approximately, one of three adults of the age of 65 or older falls every year. The World Health Organization reports that injuries due to falls are the third most common cause of chronic disability. In this paper, we proposed an approach to indoor human daily activity recognition, which combines motion and location data by using a webcam system, with a particular interest to the problem of fall detection. The proposed system identifies the face and the body in a given area, collects motion data such as face and body speeds and location data such as center of mass and aspect ratio; then the extracted parameters will be fed to a Fuzy logic classifier that classify the fall event in two classes: fall and not fall.

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Index Terms

Computer Science
Information Sciences

Keywords

Fall detection Motion data Face detection Center of mass webcam

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