Please use this identifier to cite or link to this item: https://doi.org/10.1021/ie2004779
DC FieldValue
dc.titleReview and analysis of blood glucose (BG) models for type 1 diabetic patients
dc.contributor.authorBalakrishnan, N.P.
dc.contributor.authorRangaiah, G.P.
dc.contributor.authorSamavedham, L.
dc.date.accessioned2014-10-09T07:00:38Z
dc.date.available2014-10-09T07:00:38Z
dc.date.issued2011-11-02
dc.identifier.citationBalakrishnan, N.P., Rangaiah, G.P., Samavedham, L. (2011-11-02). Review and analysis of blood glucose (BG) models for type 1 diabetic patients. Industrial and Engineering Chemistry Research 50 (21) : 12041-12066. ScholarBank@NUS Repository. https://doi.org/10.1021/ie2004779
dc.identifier.issn08885885
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/90035
dc.description.abstractBlood glucose (BG) regulation in type 1 diabetic patients has been investigated by researchers for a long time. Many mathematical models mimicking the physiological behavior of diabetic patients have been developed to predict BG variations. Models characterizing meal absorption and physical activities have also been developed in the literature, as they play a significant role in altering BG levels. Hence, existing glucose-insulin dynamic models dating back from early 1960s are reviewed along with an overview of meal absorption and exercise effect models. The available knowledge-driven BG models have been classified into different families based on their origin for development. Also, five knowledge-driven BG models (with at least one model from a family) have been analyzed by either varying basal insulin or meal ingestion. The available meal absorption models have also been simulated to compare and analyze them for different meal sizes. The major objective of the analysis is to study the BG dynamics of different models at their nominal parameter values, under varying basal insulin doses and meal ingestion. Similar analysis has been performed on 10 adult patient models in a recent benchmark simulator for comparison. These results will be useful for understanding the responses of different BG models at their nominal parameter values and for preliminary selection of a suitable treatment model(s) for a patient. © 2011 American Chemical Society.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1021/ie2004779
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.description.doi10.1021/ie2004779
dc.description.sourcetitleIndustrial and Engineering Chemistry Research
dc.description.volume50
dc.description.issue21
dc.description.page12041-12066
dc.description.codenIECRE
dc.identifier.isiut000296128300032
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