@article{ref1,
title="Two-threshold energy based fall detection using a triaxial accelerometer",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2016",
author="Sucerquia, Angela and Lopez, Jose D. and Vargas, Francisco and Sucerquia, Angela and Lopez, Jose D. and Vargas, Francisco and Sucerquia, Angela and Vargas, Francisco and Lopez, Jose D.",
volume="2016",
number="",
pages="3101-3104",
abstract="Elderly fall detection based on accelerometers is an active research area. Nowadays authors are addressing specific problems such as failure rates and energy consumption, but in most cases their strategies do not conciliate these objectives. In this paper we propose a double threshold based methodology with two novel detection features, a product between the sum vector magnitude and the signal magnitude area, and a normalization of the signal magnitude area over five 1 s windows. The methodology was validated using the public Mobifall dataset, and one developed for this work. It achieved 99 % of accuracy with Mobifall, and 97 % with the self-developed dataset. This methodology is based on an activity by activity analysis performed for determining which activities are prone to fail, as an alternative way of reducing detection failures.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2016.7591385",
url="http://dx.doi.org/10.1109/EMBC.2016.7591385"
}