@article{ref1,
title="Unobtrusive in-home detection of time spent out-of-home with applications to loneliness and physical activity",
journal="IEEE journal of biomedical and health informatics",
year="2014",
author="Petersen, Johanna and Austin, Daniel and Kaye, Jeffrey A. and Pavel, Misha and Hayes, Tamara L.",
volume="18",
number="5",
pages="1590-1596",
abstract="Loneliness is a common condition in elderly associated with severe health consequences including increased mortality, decreased cognitive function, and poor quality of life. Identifying and assisting lonely individuals is therefore increasingly important-especially in the home setting-as the very nature of loneliness often makes it difficult to detect by traditional methods. One critical component in assessing loneliness unobtrusively is to measure time spent out-of-home, as loneliness often presents with decreased physical activity, decreased motor functioning, and a decline in activities of daily living, all of which may cause decrease in the amount of time spent outside the home. Using passive and unobtrusive in-home sensing technologies, we have developed a methodology for detecting time spent out-of-home based on logistic regression. Our approach was both sensitive (0.939) and specific (0.975) in detecting time out-of-home across over 41 000 epochs of data collected from four subjects monitored for at least 30 days each in their own homes. In addition to linking time spent out-of-home to loneliness, (r = -0.44, p = 0.011) as measured by the UCLA Loneliness Index, we demonstrate its usefulness in other applications such as uncovering general behavioral patterns of elderly and exploring the link between time spent out-of-home and physical activity ( r = 0.415, p = 0.031), as measured by the Berkman Social Disengagement Index.<p /> <p>Language: en</p>",
language="en",
issn="2168-2194",
doi="10.1109/JBHI.2013.2294276",
url="http://dx.doi.org/10.1109/JBHI.2013.2294276"
}