An evolutionary methodology for estimating blood glucose levels from interstitial glucose measurements and their derivatives

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43953576" target="_blank" >RIV/49777513:23520/18:43953576 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11140/18:10384946 RIV/00669806:_____/18:10384946

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ISCC.2018.8538682" target="_blank" >http://dx.doi.org/10.1109/ISCC.2018.8538682</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISCC.2018.8538682" target="_blank" >10.1109/ISCC.2018.8538682</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An evolutionary methodology for estimating blood glucose levels from interstitial glucose measurements and their derivatives

Popis výsledku v původním jazyce

The patients suffering from diabetes are subjected to several serious medical risks that can lead also to fatal consequences. To enhance the quality of life of these patients there is the necessity to devise an artificial pancreas able to inject an insulin bolus when needed. This paper presents a genetic-programming based algorithm to extrapolate a regression model able to estimate the blood glucose (BG) level through interstitial glucose (IG) measurements and their derivatives. This algorithm represents a possible step in building the fundamental element of such an artificial pancreas, namely a new evolutionary computation-based metodology to derive a mathematical relationship between BG and IG. The proposed evolutionary automatic procedure is evaluated on a real-world database made up of both BG and IG measurements of people suffering from Type 1 diabetes. The discovered model is validated through a comparison with other techniques during the experimental phase

Název v anglickém jazyce

An evolutionary methodology for estimating blood glucose levels from interstitial glucose measurements and their derivatives

Popis výsledku anglicky

The patients suffering from diabetes are subjected to several serious medical risks that can lead also to fatal consequences. To enhance the quality of life of these patients there is the necessity to devise an artificial pancreas able to inject an insulin bolus when needed. This paper presents a genetic-programming based algorithm to extrapolate a regression model able to estimate the blood glucose (BG) level through interstitial glucose (IG) measurements and their derivatives. This algorithm represents a possible step in building the fundamental element of such an artificial pancreas, namely a new evolutionary computation-based metodology to derive a mathematical relationship between BG and IG. The proposed evolutionary automatic procedure is evaluated on a real-world database made up of both BG and IG measurements of people suffering from Type 1 diabetes. The discovered model is validated through a comparison with other techniques during the experimental phase

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2018 IEEE Symposium on Computers and Communications, ISCC2018

ISBN

978-1-5386-6950-1

ISSN

1530-1346

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1158-1163

Název nakladatele

2018 IEEE Symposium on Computers and Communications, ISCC2018

Místo vydání

Natal

Místo konání akce

Natal Brazílie

Datum konání akce

25. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—