@article{ref1,
title="Wireless slips and falls prediction system",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2012",
author="Krenzel, Devon and Warren, Steve and Li, Kejia and Natarajan, Bala and Singh, Gurdip",
volume="2012",
number="",
pages="4042-4045",
abstract="Accidental slips and falls due to decreased strength and stability are a concern for the elderly. A method to detect and ideally predict these falls can reduce their occurrence and allow these individuals to regain a degree of independence. This paper presents the design and assessment of a wireless, wearable device that continuously samples accelerometer and gyroscope data with a goal to detect and predict falls. Lyapunov-based analyses of these time series data indicate that wearer instability can be detected and predicted in real time, implying the ability to predict impending incidents.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2012.6346854",
url="http://dx.doi.org/10.1109/EMBC.2012.6346854"
}