High level control strategies for diabetes therapy

Alberto Riva, Riccardo Bellazzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The project we describe here is aimed at assisting out-patients affected by Insulin Dependent Diabetes Mellitus. Our approach exploits the usual scheme of diabetic patients management, based on (i) a periodic evaluation of the patients' metabolic control performed by the physician, and (ii) patient-tailored tables for self-adjustments of insulin dosages. Following this scheme we have defined a system built on a two-levels architecture, that can be conveniently implemented in a telemedicine context. The High Level Module exploits both medical knowledge and clinical information in order to assess an insulin protocol, defined in terms of insulin timing, type, and total amount. The High Level Module exchanges information with the Low Level Module in order to define the control actions to be taken at the low level, as well as to periodically evaluate protocol adequacy on the basis of patient data. The goal of the Low Level Module, whose characteristics can be chosen by the High-Level Module, is to suggest the next insulin dosage, depending on the actual blood glucose measurement and a certain pre-defined insulin delivery protocol. In this paper we outline the overall organization of the system and we describe in detail the methodology and the strategies exploited by the high-level module.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages185-196
Number of pages12
Volume934 LNAI
DOIs
Publication statusPublished - 1995
Event5th Conference on Artificial Intelligence in Medicine Europe, AIME 1995 - Pavia, Italy
Duration: Jun 25 1995Jun 28 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume934 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th Conference on Artificial Intelligence in Medicine Europe, AIME 1995
CountryItaly
CityPavia
Period6/25/956/28/95

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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