Volume 12, Number 1, September 2016 - DOI: http://dx.doi.org/10.21700/ijcis.2016.273


Computing and Information Sciences is a peer reviewed journal that is committed to timely publication of original research, surveying and tutorial contributions on the analysis and development of computing and information science. The journal is designed mainly to serve researchers and developers, dealing with information and computing. Papers that can provide both theoretical analysis, along with carefully designed computational experiments, are particularly welcome. The journal is published 2-3 times per year with distribution to librarians, universities, research centers, researchers in computing, mathematics, and information science. The journal maintains strict refereeing procedures through its editorial policies in order to publish papers of only the highest quality. The refereeing is done by anonymous Reviewers. Often, reviews take four months to six months to obtain, occasionally longer, and it takes an additional several months for the publication process.

DOI: http://dx.doi.org/10.21700/ijcis.2016.110

Automatic Fall Detection System using Sensing Floors

Mohamad Daher*,1,2 email: m.daher@ulf.edu.lb 
Maan El Badaoui El Najjar2
Ahmad Diab3
Mohamad Khalil3
François Charpillet4

1CRIStAL, UMR 9189, 59650 Villeneuve d'Ascq, Lille University - Science and Technology, France
2ULF - Université de Technologie et de Sciences Appliquées Libano-Française, Deddeh-Lebanon
3Azm research center in biotechnology, EDST, CRSI research center, Faculty of Engineering, Lebanese University, Lebanon
4Inria, Villers-lès-Nancy, F-54600, CNRS, Loria, UMR nº 7503, Vandœuvre-lèsNancy, Université de Lorraine, France

*Corresponding author

Received: 30 July 2016
Revised: 10 August 2016
Accepted: 14 September 2016
Published: 29 September 2016

Abstract: Automatic fall detection is a major issue in taking care of the health of elderly people and has the potential of increasing autonomy and independence while minimizing the risks of living alone. It has been an active research area due to the large demand of the healthcare association for fall detection goods. Fortunately, due to the recent fast progression in sensing technologies, fall detection system becomes prospective. It permits to monitor elders and detect their falls, and consequently provides emergency support whenever needed. This paper describes the current work of detecting falls in independent living apartments using accelerometer concealed under tiles. We present the up-to-date advancement of data collection, feature extraction, feature selection, and signal changing detection, which are essential phases of this work.

Keywords: Changing Detection; Elderly Fall Detection; Feature Extraction and Selection; Sensing Floor.

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