title: A fuzzy model of glucose regulation.
abstract: We present a detailed glucose regulation model using fuzzy inference system (FIS) descriptions of hormonal control action and the familiar Michaelis-Menten (M-M) kinetic description for glucose transport. The fuzzy M-M model is compared and contrasted with a well-known comprehensive glucose model. The two models give similar results for glucose response, endogenous glucose production, and total uptake. The fuzzy M-M model features a renal subsystem that provides 25% of the endogenous glucose production. The work demonstrates the successful application of fuzzy logic and fuzzy inference to biological modelling. The flexibility of fuzzy inference, a linguistic description technique, permits conceptually simple statements about nonlinear processes.
authors.affiliation: Biomedical and Electrical Engineering, University of Arkansas, Fayetteville 72701, USA.
authors.forename: Em
authors.initials: E
authors.lastname: Ward
authors.forename: Terry
authors.initials: T
authors.lastname: Martin
mesh_terms: D001692:Biological Transport; D017143:Fuzzy Logic; D005947:Glucose / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological
chemical_list: D005947:Glucose