NDLI: Data mining for blood glucose prediction and knowledge discovery in diabetic patients: The METABO diabetes modeling and management system

Content Provider	IEEE Xplore Digital Library
Author	Georga, E. Protopappas, V. Guillen, A. Fico, G. Ardigo, D. Arredondo, M.T. Exarchos, T.P. Polyzos, D. Fotiadis, D.I.
Copyright Year	2009
Description	Author affiliation: The Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Greece, GR 45110 (Georga, E.; Guillen, A.; Exarchos, T.P.; Fotiadis, D.I.) \|\| Lifestyle Supporting Technologies Group, Technical University of Madrid, ES 28040 (Fico, G.) \|\| Department of Internal Medicine and Biomedical Sciences, University of Parma, Parma, Italy, IT 43100 (Ardigo, D.) \|\| Department of Mechanical Engineering and Aeronautics, University of Patras, Greece, GR 26500 (Protopappas, V.; Polyzos, D.) \|\| The Lifestyle Supporting Technologies Group, Technical University of Madrid, ES 28040 (Arredondo, M.T.)
Abstract	METABO is a diabetes monitoring and management system which aims at recording and interpreting patient's context, as well as, at providing decision support to both the patient and the doctor. The METABO system consists of (a) a Patient's Mobile Device (PMD), (b) different types of unobtrusive biosensors, (c) a Central Subsystem (CS) located remotely at the hospital and (d) the Control Panel (CP) from which physicians can follow-up their patients and gain also access to the CS. METABO provides a multi-parametric monitoring system which facilitates the efficient and systematic recording of dietary, physical activity, medication and medical information (continuous and discontinuous glucose measurements). Based on all recorded contextual information, data mining schemes that run in the PMD are responsible to model patients' metabolism, predict hypo/hyper-glycaemic events, and provide the patient with short and long-term alerts. In addition, all past and recently-recorded data are analyzed to extract patterns of behavior, discover new knowledge and provide explanations to the physician through the CP. Advanced tools in the CP allow the physician to prescribe personalized treatment plans and frequently quantify patient’s adherence to treatment.
Starting Page	5633
Ending Page	5636
File Size	709432
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5333635
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Diabetes Data mining Blood Sugar Predictive models Knowledge management Patient monitoring Remote monitoring Medical treatment Health information management
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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