@article{ref1,
title="An elderly fall detection using a wrist-worn accelerometer and barometer",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2017",
author="Jatesiktat, Prayook and Wei Tech Ang, ",
volume="2017",
number="",
pages="125-130",
abstract="As the world population is growing toward an aging society, elderly fall becomes a serious problem. Automatic fall detection and alert systems could shorten their waiting time after a fall and mitigate its physical and mental negative consequences. This work proposes a method that integrates a 3-axis accelerometer and a barometer on a wrist-worn device for the fall detection task. The method focuses on the use of noisy signals from a barometer in both pre-processing steps and feature extractions. A use of free falling events to address the lack of training data in a learning process is also explored. An evaluation using simulated falls and various activities shows a high classification performance except for a few false alarms occurring when sitting on the floor from a standing pose.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2017.8036778",
url="http://dx.doi.org/10.1109/EMBC.2017.8036778"
}