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Lifestyle monitoring as a predictive tool in telecare

Hanson, J.; Osipovic, D.; Hine, N.; Amaral, T.; Curry, R.; Barlow, J.; (2007) Lifestyle monitoring as a predictive tool in telecare. Journal of Telemedicine and Telecare , 13 (1) pp. 26-28. 10.1258/135763307781645040. Green open access

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Abstract

Six people with multiple health problems living in an extra care housing scheme for older people with vision impairment agreed to take part in a telecare trial. An average of 14.8 sensors was installed in each of the flats. The monitoring period began in January 2006 and lasted for 10 months. The data acquired by the sensors installed in each flat was transmitted from the home unit to a central computer. Four interviews were conducted with each participant. Halfway through the study we created a number of case studies of sensor activity at the time of known events in the lives of the participants, together with an attempt to interpret these patterns of activity with the benefit of available contextual information. Although our investigation showed that sensors are capable of identifying some changes in daily routines at the time of important events, the interpretation of such changes requires a large amount of contextual information and the involvement of participants themselves. Various technical and operational difficulties will need to be resolved before it will be possible to use lifestyle monitoring predictively.

Type: Article
Title: Lifestyle monitoring as a predictive tool in telecare
Open access status: An open access version is available from UCL Discovery
DOI: 10.1258/135763307781645040
Publisher version: http://dx.doi.org/10.1258/135763307781645040
Language: English
Additional information: This article is an updated version of the conference paper presented at "TeleMed and eHealth '06: transforming the patient experience"
UCL classification:
URI: https://discovery.ucl.ac.uk/id/eprint/3424
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