@article{ref1,
title="Artificial neural networks as an alternative to traditional fall detection methods",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2013",
author="Vallejo, Marcela and Isaza, Claudia V. and Lopez, Jose D.",
volume="2013",
number="",
pages="1648-1651",
abstract="Falls are common events among older adults and may have serious consequences. Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). This method intends to improve fall detection accuracy, by avoiding the traditional threshold - based fall detection methods, and introducing ANN as a suitable option on this application.Also ANN have low computational cost, this characteristic makes them easy to implement on a portable device, comfortable to be wear by the patient.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2013.6609833",
url="http://dx.doi.org/10.1109/EMBC.2013.6609833"
}