NDLI: Fall detector system based on wristwatch and artificial neural network

Content Provider	IEEE Xplore Digital Library
Author	Bougueroua, L. Dhouib, M. A. Medjahed, H. Mabrouk, K.
Copyright Year	2011
Description	Author affiliation: Esigetel, 1 rue du port de valvins, 77210, Avon, France (Bougueroua, L.; Dhouib, M. A.; Mabrouk, K.) \|\| Esigetel 1 rue du port de valvins 77210, Avon, France (Medjahed, H.)
Abstract	The age of the population is increasing in all societies throughout the world (for example in Europe life expectancy for men is about 71 years and for women about 79 years). Elderly people prefer to preserve their independence, autonomy and way of life by living at home as long as possible. In order to improve the quality of life of the elderly several applications has been developed: home monitoring in order to detect distress situations, and audio-video transmission in order to allow specialists to diagnose patients remotely. The purpose of this article is to present a fall detector application for the elderly. Our proposal seeks a solution to the problems of acceptability, convenience and simplicity of the device in the analysis of the final users. After considering many possibilities we have decided that a wristwatch was the most suitable solution.
Starting Page	1
Ending Page	4
File Size	235106
Page Count	4
File Format	PDF
ISBN	9781457700170
ISSN	19460759
e-ISBN	9781457700187
e-ISBN	9781457700163
DOI	10.1109/ETFA.2011.6059218
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-05
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Acceleration Biological neural networks Senior citizens Accelerometers Detectors Monitoring Biomedical monitoring
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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