@article{ref1,
title="Automatic detection of falling of the elderly subject among his daily activities",
journal="Annual International Conference of the IEEE Engineering in Medicine and Biology Society.",
year="2022",
author="Noury, N.",
volume="2022",
number="",
pages="2421-2425",
abstract="Most elderly patients after falling, being not able to rise up or call for help, are particularly at risk of complication. This urges for the development of autonomous devices for earliest detection of falls. This paper is an overview of the current design approaches to autonomous fall detectors - sensors and algorithms- and a methodology to assess their efficiency. We then propose our fall sensor, which features high sensitivity (95%) and specificity (99%) on simulated falls in lab settings, and lower sensitivity (62.5%) in real settings in a group of 10 patients, with 8 falls detected over a period of 28 days.<p /> <p>Language: en</p>",
language="en",
issn="2375-7477",
doi="10.1109/EMBC48229.2022.9871367",
url="http://dx.doi.org/10.1109/EMBC48229.2022.9871367"
}