DocumentCode :
1193019
Title :
A Novel Blood Glucose Regulation Using TSK 
-FCMAC: A Fuzzy CMAC Based on the Zero-Ordered TSK Fuzzy Inference Scheme
Author :
Ting, Chan Wai ; Quek, Chai
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
Volume :
20
Issue :
5
fYear :
2009
fDate :
5/1/2009 12:00:00 AM
Firstpage :
856
Lastpage :
871
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.
Keywords :
blood; cerebellar model arithmetic computers; fuzzy neural nets; fuzzy reasoning; learning (artificial intelligence); medical computing; medical control systems; medical disorders; neurocontrollers; blood glucose regulation; cerebellar model articulation controller; dietary profile; fuzzy CMAC; glucose-insulin dynamics; localized online training; type I insulin-dependent diabetes mellitus patient; zero-ordered Takagi-Sugeno-Kang fuzzy inference scheme; Blood glucose regulation; TSK $^{0}$ -FCMAC; Takagi–Sugeno–Kang (TSK) fuzzy inference scheme; diabetes type I; dietary profile; intra- and interpatient metabolic variation; localized memory structure; model reference neural adaptive control; Adult; Algorithms; Artificial Intelligence; Blood Glucose; Computer Simulation; Diabetes Mellitus, Type 1; Diet; Fuzzy Logic; Glucose; Humans; Insulin; Insulin Infusion Systems; Male; Models, Biological; Neural Networks (Computer); Time;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2008.2011735
Filename :
4801524
Link To Document :
