creators_name: Walsh, Lorcan
creators_name: Kealy, Andrea
creators_name: Loane, John
creators_name: Doyle, Julie
creators_name: Bond, Rodd
creators_id: lorcan.walsh@casala.ie
creators_id: andrea.kealy@casala.ie
creators_id: john.loane@casala.ie
creators_id: julie.doyle@casala.ie
creators_id: rodd.bond@netwellcentre.org
type: conference_item
datestamp: 2016-11-29 11:49:45
lastmod: 2016-11-29 11:49:45
metadata_visibility: show
title: Inferring Health Metrics from Ambient Smart Home Data
ispublished: pub
subjects: subject_computerscience
subjects: subject_elderly
full_text_status: public
pres_type: paper
keywords: Smart home technology; Ambient sensors; Older people; Quality of life.
abstract: As the population ages, smart home technology and applications are expected to support older adults to age in place and reduce the associated economic and societal burden. This paper describes a study where the relationship between ambient sensors, permanently deployed as part of smart aware apartments, and clinically validated health questionnaires is investigated. 27 sets of ambient data were taken from a 28 day block from 13 participants all of whom were over 60 years old. Features derived from ambient sensor data were found to be significantly correlated to measures of anxiety, sleep quality, depression, loneliness, cognition, quality of life and independent living skills (IADL). Subsequently, linear discriminant analysis was shown to predict participants suffering from increased anxiety and loneliness with a high accuracy (�70%). While the number of participants is small, this study reports that objective ambient features may be used to infer clinically validated health metrics. Such findings may be used to inform interventions for active and healthy ageing.
date: 2014
date_type: published
event_title: IEEE International Conference on Bioinformatics and Biomedicine
event_dates: 2014
event_type: conference
refereed: TRUE
citation:   Walsh, Lorcan and Kealy, Andrea and Loane, John and Doyle, Julie and Bond, Rodd  (2014) Inferring Health Metrics from Ambient Smart Home Data.  In: IEEE International Conference on Bioinformatics and Biomedicine, 2014.     
document_url: http://eprints.dkit.ie/553/1/Walsh%20-%20Inferring%20health%20metrics.....pdf