Statistical analysis of the blood glucose data for automated diagnosis

  • Authors:

  • Eugen Iancu;Ionela Iancu;Maria Mota

  • Affiliations:

  • Department of Automation, University of Craiova, Craiova;Department of Physiology, Medical Informatics and Biostatistics, University of Medicine and Pharmacy of Craiova, Craiova, Romania;Department of Diabetes and Nutrition Diseases, University of Medicine and Pharmacy of Craiova, Craiova, Romania

  • Venue:
  • MCBC'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Biology & Chemistry
  • Year:
  • 2008

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Abstract

The mellitus diabetes is a disease with serious social implications through the large number of people affected, complications and high costs that it involves. The introduction in the medical practice of the blood glucose continuous monitoring systems has made possible the automated analyse of blood glucose dynamics. Along this paper the authors present algorithms for automatic diagnosis in the diabetic patients monitoring with applications, especially in the intensive care units and telemedicine. We have focused on the statistical analysis methods in order to detect the reliable characteristics, useful in the identification of standard aspects or stable patterns for each type and stage of the complex and long-term evolution of the disease that is diabetes mellitus.