Data Fusion and Aggregation Methods for Pre-Processing Ambulatory Monitoring and Remote Sensor Data for Upload to Personal Electronic Health Records

Moulton, BD; Chaczko, ZC; Karatovic, M

Data Fusion and Aggregation Methods for Pre-Processing Ambulatory Monitoring and Remote Sensor Data for Upload to Personal Electronic Health Records

Moulton, BD Chaczko, ZC

Karatovic, M

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Publisher:: Advanced Institute of Convergence IT
Publication Type:: Journal Article
Citation:: International Journal of Digital Content Technology a..., 2009, 3 (4), pp. 120 - 127
Issue Date:: 2009-01

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Field	Value	Language
dc.contributor.author	Moulton, BD	en_US
dc.contributor.author	Chaczko, ZC https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Karatovic, M	en_US
dc.date.issued	2009-01	en_US
dc.identifier.citation	International Journal of Digital Content Technology a..., 2009, 3 (4), pp. 120 - 127	en_US
dc.identifier.issn	1975-9339	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10596
dc.description.abstract	Several countries including Australia are developing standards for personal electronic health records, and in many cases the standards provide ways for patients to upload data from their own sensor systems to their electronic health records. This article explores issues relating to the design of systems where electronic medical records are updated with data or meta-data from in-home or on-body health monitoring sensor systems. A prototype system was designed, implemented and subsequently evaluated in a way intended to further understanding regarding collection and transfer of sensor data to an electronic health record. A key issue that arose was the extent to which levels of confidence in the data may be affected by the type, quality, installation, maintenance and calibration of the sensors.	en_US
dc.publisher	Advanced Institute of Convergence IT	en_US
dc.relation.ispartof	International Journal of Digital Content Technology a...	en_US
dc.title	Data Fusion and Aggregation Methods for Pre-Processing Ambulatory Monitoring and Remote Sensor Data for Upload to Personal Electronic Health Records	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	3	en_US
utslib.for	200102 Communication Technology and Digital Media Studies	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0807 Library and Information Studies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.issue	4	en_US
pubs.volume	3	en_US

Abstract:

Several countries including Australia are developing standards for personal electronic health records, and in many cases the standards provide ways for patients to upload data from their own sensor systems to their electronic health records. This article explores issues relating to the design of systems where electronic medical records are updated with data or meta-data from in-home or on-body health monitoring sensor systems. A prototype system was designed, implemented and subsequently evaluated in a way intended to further understanding regarding collection and transfer of sensor data to an electronic health record. A key issue that arose was the extent to which levels of confidence in the data may be affected by the type, quality, installation, maintenance and calibration of the sensors.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/10596