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Application of Fuzzy Logic Control for Regulation of Glucose Level of Diabetic Patient

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Machine Learning in Healthcare Informatics

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 56))

Abstract

Diabetes can lead to many complications. If a patient cannot control his or her glucose level properly, he or she may suffer serious consequences. The result may be ketosis, which is normally due to an increase of acetone (a toxic acid product) and may lead to a situation such as diabetic coma. A fuzzy logic control system for the regulation of glucose level for diabetic patients is proposed in this chapter. A mathematical model describing the relationship between the human glucose level, insulin, and food is first presented. Then, a generalized fuzzy logic controller, including a set of fuzzy logic rules, is introduced to regulate glucose levels for diabetic patients. Following the fuzzy logic controller, simulation is presented. The results show that the fuzzy logic control is effective for handling the glucose level based on feedback scheme.

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Author information

Authors and Affiliations

  1. Department of Electronic and Computer Engineering, Ngee Ann Polytechnic, Singapore, 599489, Republic of Singapore

    K. Y. Zhu & W. D. Liu

  2. Information and Communication Department, Shenyang University of Chemical Technology, Shenyang, China

    Y. Xiao

Authors
  1. K. Y. Zhu
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  2. W. D. Liu
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  3. Y. Xiao
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Corresponding author

Correspondence to K. Y. Zhu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Louisiana Tech University, Ruston, Louisiana, USA

    Sumeet Dua

  2. Ngee Ann Polytechnic, Singapore, Singapore

    U. Rajendra Acharya

  3. Department of Health Informatics and Information Management, Louisiana Tech University, Ruston, Louisiana, USA

    Prerna Dua

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© 2014 Springer-Verlag Berlin Heidelberg

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Zhu, K.Y., Liu, W.D., Xiao, Y. (2014). Application of Fuzzy Logic Control for Regulation of Glucose Level of Diabetic Patient. In: Dua, S., Acharya, U., Dua, P. (eds) Machine Learning in Healthcare Informatics. Intelligent Systems Reference Library, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40017-9_3

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  • DOI: https://doi.org/10.1007/978-3-642-40017-9_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40016-2

  • Online ISBN: 978-3-642-40017-9

  • eBook Packages: EngineeringEngineering (R0)

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