A novel blood glucose regulation using TSK0-FCMAC: a fuzzy CMAC based on the zero-ordered TSK fuzzy inference scheme.
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.
Ting
Chan Wai
CW
Centre of Computational Intelligence, School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore. tingchanwai@pmail.ntu.edu.sg
Quek
Chai
C
D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001786:Blood Glucose / Q000378:metabolism*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000188:drug therapy; D004032:Diet; D017143:Fuzzy Logic; D005947:Glucose / Q000378:metabolism; D006801:Humans; D007328:Insulin / Q000097:blood / Q000378:metabolism / Q000627:therapeutic use; D007332:Insulin Infusion Systems; D008297:Male; D008954:Models, Biological; D016571:Neural Networks, Computer; D013995:Time
D001786:Blood Glucose; D007328:Insulin; D005947:Glucose