This paper employs a new approach to regulate the blood glucose level of type I diabetic patient under an intensive insulin treatment. The closed-loop control scheme incorporates expert knowledge about treatment by using reinforcement learning theory to maintain the normoglycemic average of 80 mg/dl and the normal condition for free plasma insulin concentration in severe initial state. The insulin delivery rate is obtained off-line by using Qlearning algorithm, without requiring an explicit model of the environment dynamics. The implementation of the insulin delivery rate, therefore, requires simple function evaluation and minimal online computations. Controller performance is assessed in terms of its ability to reject the effect of meal disturbance and to overcome the variability in the glucose-insulin dynamics from patient to patient. Computer simulations are used to evaluate the effectiveness of the proposed technique and to show its superiority in controlling hyperglycemia over other existing algorithms


    Access

    Download


    Export, share and cite



    Title :

    Agent-based Simulation for Blood Glucose Control in Diabetic Patients


    Contributors:

    Publication date :

    2009-09-24


    Remarks:

    oai:zenodo.org:1060215



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




    INTERNAL MODEL CONTROL DESIGN FOR BLOOD GLUCOSE REGULATION IN A TYPE 1 DIABETIC PATIENT

    Araromi, D. O. / Agarry, S. E. / Onifade, D. V. | BASE | 2014

    Free access

    Blood Glucose Regulation for Type 1 Diabetic Patients at Intensive Care Unit via Continuous Sliding-Mode Algorithms

    Franco, Roberto / Ríos, Héctor / Ferreira de Loza, Alejandra et al. | Springer Verlag | 2023


    An Agent-Based Simulation of Blood Coagulation Processes

    Yazdanbod, Iman / Marcus, S. | BASE | 2011

    Free access

    Simulation of glucose regulating mechanism with an agent-based software engineering tool

    Emek, Sevcan / Evren, Vedat / Bora, Şebnem | BASE | 2019

    Free access