@article{ref1,
title="Embedded fall and activity monitoring for a wearable ambient assisted living solution for older adults",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2012",
author="Bourke, Alan K. and Prescher, Sandra and Koehler, Friedrich and Cionca, Victor and Tavares, Carlos and Gomis, Sergi and Garcia, Virginia and Nelson, John",
volume="2012",
number="",
pages="248-251",
abstract="With the rapidly increasing over 60 and over 80 age groups in society, greater emphasis will be put on technology to detect emergency situations, such as falls, in order to promote independent living. This paper describes the development and deployment of fall-detection, activity classification and energy expenditure algorithms, deployed in a tele-monitoring system. These algorithms were successfully tested in an end-user trial involving 9 elderly volunteers using the system for 28 days.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2012.6345916",
url="http://dx.doi.org/10.1109/EMBC.2012.6345916"
}