@article{ref1,
title="Pilot evaluation of an unobtrusive system to detect falls at nighttime",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2014",
author="Redmond, Stephen J. and Zhaonan Zhang,  and Narayanan, Michael R. and Lovell, Nigel H.",
volume="2014",
number="",
pages="1756-1759",
abstract="Research shows that older people (aged 65 years and over) suffer many unintentional indoor falls which often lead to severe injuries. As a result of an increasingly aged population in developed countries, a sizable portion of healthcare funding is consumed in the treatment of fall-related injuries and associated long-term care. Detecting falls soon after they occur can be potentially live saving. In addition, early treatment of fall-related injuries can reduce treatment costs by minimizing health deterioration resulting from long periods spent incapacitated on the floor after a fall (a scenario known as a 'long lie') and decreasing the number of hospital bed-days required. In this study, a previously proposed unobtrusive nighttime fall detection system based on wireless passive infrared sensors and furniture load sensors is evaluated in a pilot study involving three older subjects, monitored for a combined total of 174 days. No falls occurred during the study. The system reported a false alarm rate of 0.53 falls per day, which is comparable with similar unobtrusive and wearable sensor fall detection solutions.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2014.6943948",
url="http://dx.doi.org/10.1109/EMBC.2014.6943948"
}