Sensor drift compensation using fuzzy interference system and sparse-grid quadrature filter in blood glucose control

Péter Szalay, László Szilágyi, Zoltán Benyó, Levente Kovács

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

1 Citation (Scopus)

Abstract

Diabetes mellitus is a serious chronic condition of the human metabolism. The development of an automated treatment has reached clinical phase in the last few years. The goal is to keep the blood glucose concentration within a certain region with minimal interaction required by the patient or medical personnel. However, there are still several practical problems to solve. One of these would be that the available sensors have significant noise and drift. The latter is rather difficult to manage, because the deviating signal can cause the controller to drive the glucose concentration out of the safe region even in the case of frequent calibration. In this study a linear-quadratic-Gaussian (LQG) controller is employed on a widely used diabetes model and enhanced with an advanced Sparse-grid quadratic filter and a fuzzy interference system-based calibration supervisor.

Original languageEnglish
Title of host publicationNeural Information Processing - 21st International Conference, ICONIP 2014, Proceedings
EditorsKok Wai Wong, Chu Kiong Loo, Kaizhu Huang, Keem Siah Yap, Andrew Teoh
PublisherSpringer Verlag
Pages445-453
Number of pages9
ISBN (Electronic)9783319126395
Publication statusPublished - Jan 1 2014
Event21st International Conference on Neural Information Processing, ICONIP 2014 - Kuching, Malaysia
Duration: Nov 3 2014Nov 6 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8835
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Conference on Neural Information Processing, ICONIP 2014
CountryMalaysia
CityKuching
Period11/3/1411/6/14

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Keywords

  • Diabetes
  • Fuzzy inference system
  • LQG control
  • Sparse-grid quadratic filter

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Szalay, P., Szilágyi, L., Benyó, Z., & Kovács, L. (2014). Sensor drift compensation using fuzzy interference system and sparse-grid quadrature filter in blood glucose control. In K. W. Wong, C. K. Loo, K. Huang, K. S. Yap, & A. Teoh (Eds.), Neural Information Processing - 21st International Conference, ICONIP 2014, Proceedings (pp. 445-453). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8835). Springer Verlag.