Assessment of type II diabetes mellitus
department or school: Applied Science, Faculty of
data provider: DSpace
degree campus: UBCV
creator: Barazandegan, Melissa
issued: 2017-01-21T03:51:01
issued: 2016
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Several methods have been proposed to evaluate a person's insulin sensitivity (ISI). However, all are neither easy nor inexpensive to implement. Therefore, the purpose of this research is to develop a new ISI that can be easily and accurately obtained by patients themselves without costly, time consuming and inconvenient testing methods. In this thesis, the proposed testing method has been simulated on the computerized model of the type II diabetic-patients to estimate the ISI. The proposed new ISI correlates well with the ISI called M-value obtained from the gold standard but elaborate euglycemic hyperinsulinemic clamp (r = 0.927, p = 0.0045). In this research, using a stochastic nonlinear state-space model, the insulin-glucose dynamics in type II diabetes mellitus is modeled. If only a few blood glucose and insulin measurements per day are available in a non-clinical setting, estimating the parameters of such a model is difficult. Therefore, when the glucose and insulin concentrations are only available at irregular intervals, developing a predictive model of the blood glucose of a person with type II diabetes mellitus is important. To overcome these difficulties, under various levels of randomly missing clinical data, we resort to online Sequential Monte Carlo estimation of states and parameters of the state-space model for type II diabetic patients. This method is efficient in monitoring and estimating the dynamics of the peripheral glucose, insulin and incretins concentration when 10%, 25% and 50% of the simulated clinical data were randomly removed. Variabilities such as insulin sensitivity, carbohydrates intake, exercise, and more make controlling blood glucose level a complex problem. In patients with advanced TIIDM, the control of blood glucose level may fail even under insulin pump therapy. Therefore, building a reliable model-based fault detection (FD) system to detect failures in controlling blood glucose level is critical. In this thesis, we propose uti…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/59826
note: Assessment of Type II DiabetesMellitusbyMelissa BarazandeganB.Sc., Sharif University of Technology, 2007M.Sc., Sharif University of Technology, 2009A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Chemical and Biological Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)November 2016c© Melissa Barazandegan 2016AbstractSeveral methods have been proposed to evaluate a personâs insulin sensitivity (ISI). How-ever, all are neither easy nor inexpensive to implement. Therefore, the purpose of thisresearch is to develop a new ISI that can be easily and accurately obtained by patientsthemselves without costly, time consuming and inconvenient testing methods. In this the-sis, the proposed testing method has been simulated on the computerized model of the typeII diabetic-patients to estimate the ISI. The proposed new ISI correlates well with the ISIcalled M-value obtained from the gold standard but elaborate euglycemic hyperinsulinemicclamp (r = 0.927, p = 0.0045).In this research, using a stochastic nonlinear state-space model, the insulin-glucose dy-namics in type II diabetes mellitus is modeled. If only a few blood glucose and insulinmeasurements per day are available in a non-clinical setting, estimating the parametersof such a model is difficult. Therefore, when the glucose and insulin concentrations areonly available at irregular intervals, developing a predictive model of the blood glucose ofa person with type II diabetes mellitus is important. To overcome these difficulties, undervarious levels of randomly missing clinical data, we resort to online Sequential Monte Carloestimation of states and parameters of the state-space model for type II diabetic patients.This method is efficient in monitoring and estimating the dynamics of the peripheral glu-cose, insulin and incretins concentration when 10%, 25% and 50% of the simulated clinicaldata were randomly removed.i…
has type: Thesis/Dissertation
date issued: 2017-02
is shown at: 10.14288/1.0339984
language: eng
degree discipline: Chemical and Biological Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/59826