Abstract
Lifestyle monitoring as a subset of telecare sets out to
use information derived from a range of sensors to put in place a
profile of individual behaviour against which changes in
behaviour can be compared and referenced to detect variations
indicative of a change in health status and need. Based on their
research, the authors suggest that in order for lifestyle
monitoring to develop, there is a need to more fully understand
the way in which such systems operate and how the various
aspects such as data collection through to analysis and
interpretation come together. The paper therefore presents
elements of a system structure for lifestyle monitoring and
shows how this structure can incorporate a range of approaches
to interpretation and analysis, illustrating this with reference to
practical trials involving numeric, analytic and statistical
methods as well as a machine learning based approach.
Original language | English |
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Title of host publication | 1st IEEE Conference on Healthcare Informatics, Imaging and Systems Biology |
Publisher | IEEE |
Pages | 213-220 |
Number of pages | 8 |
ISBN (Electronic) | 9780695-44076 |
ISBN (Print) | 9781457703256 |
DOIs | |
Publication status | Published - 27 Oct 2011 |
Externally published | Yes |
Event | First IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology - IBM Almaden Research Center, San Jose, United States Duration: 26 Jul 2011 → 29 Jul 2011 |
Conference
Conference | First IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology |
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Abbreviated title | HISB 2011 |
Country/Territory | United States |
City | San Jose |
Period | 26/07/11 → 29/07/11 |
Keywords
- Computerised monitoring
- Health information management
- Machine intelligence
- Public healthcare