title: Synthesis of insulin pump controllers from safety specifications using Bayesian model validation.
abstract: Insulin pump controllers seek to alleviate the chronic suffering caused by diabetes that affects over 6% of the world population. The design of control laws for insulin pump controllers has been well studied. However, the parameters involved in the control law are difficult to synthesize. Traditionally, ad hoc approaches using animal models and random sampling have been used to construct these parameters. We suggest a synthesis algorithm that uses Bayesian statistical model validation to reduce the number of simulations needed. We apply this algorithm to the problem of insulin pump controller synthesis using in silico simulation of the glucose-insulin metabolism model.
authors.affiliation: EECS Department, University of Central Florida, Orlando, FL 32816, USA.
authors.forename: Sumit Kumar
authors.initials: SK
authors.lastname: Jha
authors.forename: Raj Gautam
authors.initials: RG
authors.lastname: Dutta
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Langmead
authors.forename: Susmit
authors.initials: S
authors.lastname: Jha
authors.forename: Emily
authors.initials: E
authors.lastname: Sassano
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001786:Blood Glucose / Q000378:metabolism; D007328:Insulin / Q000378:metabolism*; D007332:Insulin Infusion Systems / Q000592:standards*
chemical_list: D001786:Blood Glucose; D007328:Insulin