NDLI: A Novel Blood Glucose Regulation Using TSK<formula formulatype=inline><tex Notation=TeX>$^{0}$</tex></formula>-FCMAC: A Fuzzy CMAC Based on the Zero-Ordered TSK Fuzzy Inference Scheme

Content Provider	IEEE Xplore Digital Library
Author	Chan Wai Ting Chai Quek
Copyright Year	1990
Abstract	This paper presents a novel blood glucose regulation for type I (insulin-dependent) diabetes mellitus patients using biologically inspired TSK⁰-FCMAC, a fuzzy cerebellar model articulation controller (CMAC) based on the zero-ordered Takagi-Sugeno-Kang (TSK) fuzzy inference scheme. TSK⁰-FCMAC is capable of performing localized online training with an effective fuzzy inference scheme that could respond swiftly to changing environment such as human's endocrine system. Without prior knowledge of disturbance (e.g., food intake), the proposed fuzzy CMAC is able to capture the glucose-insulin dynamics of individuals under different dietary profiles. Preliminary simulations show that the blood glucose level is kept within the state of euglycemia. The design of the proposed system follows closely to what is available in real life and is suitable for animal and clinical pilot testing in the near future.
Sponsorship	IEEE Computational Intelligence Society
Page Count	16
File Size	2532104
Starting Page	856
Ending Page	871
File Format	PDF
ISSN	10459227
Volume Number	20
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blood Sugar Fuzzy control Diabetes Biological system modeling Biological control systems Takagi-Sugeno-Kang model Fuzzy systems Endocrine system Animals TSK $^{0}$-FCMAC Blood glucose regulation diabetes type I dietary profile intra- and interpatient metabolic variation localized memory structure model reference neural adaptive control Takagi–Sugeno–Kang (TSK) fuzzy inference scheme
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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