Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Innovative Biosystem...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Innovative Biosystems and Bioengineering
Article . 2021 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Innovative Biosystems and Bioengineering
Article
License: CC BY
Data sources: UnpayWall
versions View all 1 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Algorithm for Predicting the Glicemic Profil in Diabetes Under Regular Measurements

Authors: Svitlana Kiforenko; Igor Vasyliev; Mykola Lavrenyuk; Tatiana Hontar;

Algorithm for Predicting the Glicemic Profil in Diabetes Under Regular Measurements

Abstract

Background. In recent years, modern technical devices have been created so that to use in the practice of treating diabetes mellitus. These are systems for continuous monitoring of glycemia, which is a significant addition to the widely accepted measurements of glucose levels with a glucometer, various infusion systems, which significantly improve the doctor's decision-making process. However, such technical means are quite expensive and inaccessible to a wide range of users. In addition, their use is associated with both adverse reactions when wearing them and with patient compliance issues. In this case an alternative can be using mathematical modeling tools. Objective. The aim of the paper is to prove the possibility of using mathematical modeling to predict the glycemic profile as a certain degree of alternative to a sensor for continuous monitoring of blood glucose levels under conditions of limited irregular measurements. Methods. To solve the problem it is proposed to employ the technology of mathematical modeling. The structure of the model makes it possible to implement the mathematical formalism by analytical formulae. Results. As a result, the insulin-glucose-tolerance test has been developed that allows quantitatively assessing a patient's personal sensitivity to insulin-bolus therapy. We proposed the mathematical model for solving the problem by analytical formulae. Algorithms for identifying model parameters, an algorithm for calculating the insulin dose that compensates for the carbohydrate component in the intended meal, and an algorithm for predicting the daily glycemic profile have been developed. The software-algorithmic structure for the implementation of the mathematical formalism has been developed. Conclusions. The conducted simulation study employing the technology of mathematical modeling makes it possible to evaluate the functioning of the developed procedures at the preclinical stage. The simplicity of calculations using analytical formulae can be a prerequisite for the implementation of the algorithm in portable autonomous special-purpose devices or in smartdata under the Android OS, which is a definite contribution to development of digital diabetology.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold