Research Article
Derivation of Night Time Behaviour Metrics using Ambient Sensors
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252095, author={Andrea Kealy and Kevin McDaid and John Loane and Lorcan Walsh and Julie Doyle}, title={Derivation of Night Time Behaviour Metrics using Ambient Sensors}, proceedings={7th International Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2013}, month={5}, keywords={aal aging in place ambient monitoring sleep measures}, doi={10.4108/icst.pervasivehealth.2013.252095} }- Andrea Kealy
Kevin McDaid
John Loane
Lorcan Walsh
Julie Doyle
Year: 2013
Derivation of Night Time Behaviour Metrics using Ambient Sensors
PERVASIVEHEALTH
ICST
DOI: 10.4108/icst.pervasivehealth.2013.252095
Abstract
Sleep problems have been shown to have significant negative impact on health. As such it is important to examine night time behaviour to objectively determine when sleep disturbances arise. Due to the large night-to-night variability in sleep quality for older adults, it is important to objectively measure behaviour over a significant period to establish trends or changes in patterns of sleep. In this paper we present a means of ambiently monitoring sleep through the use of sensors installed in each of sixteen independent living apartments. We investigate the effect of time outside the home and movement within the home on sleep. These measures are validated against comparative measures from two actigraph datasets. The first consisting of five adults, two of whom are healthy subjects and the other three adults have previously fallen, gathered over a period of between two and four nights. The second consisting of three older adults recorded over seven nights in their own homes. Results relating time outside the home and movement within the home to sleep are presented for three individuals spanning a period of between 630 and 650 days.