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  4. Model-based insulin therapy scheduling: A mixed-integer nonlinear dynamic optimization approach
 
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Model-based insulin therapy scheduling: A mixed-integer nonlinear dynamic optimization approach

Journal
Industrial and Engineering Chemistry Research
Journal Volume
48
Journal Issue
18
Pages
8595-8604
Date Issued
2009
Author(s)
Chen C.-L.  
Tsai H.-W.
DOI
10.1021/ie9005673
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/409675
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349309895&doi=10.1021%2fie9005673&partnerID=40&md5=3b0ae12174dcf58bc059ad1d6cc291d8
Abstract
This article aims at developing a better insulin injection scheduling strategy for diabetes. For this purpose, the subcutaneous (sc) absorption behaviors of available insulin and the overall glucose-insulin dynamics for diabetes are investigated at first. Therein several sets of clinical data from literature are applied to verify the overall glucose-insulin dynamic models through parametric estimation. The problem of searching the optimal injected time, type, and dosage of insulin are then formulated as a mixed-integer nonlinear dynamic program (MINDP). The optimal injection schedules are consequently found for a 24 h cycle in three scenarios by adjusting either the insulin injection times, or insulin types, or insulin dosage, or other combinations of these factors. The corresponding improvement in glycemia control in each scenario is demonstrated. The robustness of suggested therapy schedules to inconsistency of scheduled situations is finally exemplified. It is expected that the proposed optimal therapy scheduling can serve as a valuable reference for physicians and patients to take better glucose control on a daily basis. ? 2009 American Chemical Society.
SDGs

[SDGs]SDG3

Other Subjects
Absorption behaviors; Clinical data; Glucose control; Glycemia; Insulin dosage; Insulin dynamics; Insulin injections; Insulin therapy; Model-based; Non-linear dynamics; Optimal injection; Parametric estimation; Scheduling strategies; Therapy scheduling; Glucose; Integer programming; Optimization; Parameter estimation; Scheduling; Three term control systems; Insulin
Type
journal article

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