SmartCGMS as a Testbed for a Blood-Glucose Level Prediction and/or Control Challenge with (an FDA-Accepted) Diabetic Patient Simulation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43961666" target="_blank" >RIV/49777513:23520/20:43961666 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1877050920323164" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050920323164</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2020.10.048" target="_blank" >10.1016/j.procs.2020.10.048</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SmartCGMS as a Testbed for a Blood-Glucose Level Prediction and/or Control Challenge with (an FDA-Accepted) Diabetic Patient Simulation

Popis výsledku v původním jazyce

Diabetic patient desires to avoid hypo- and hyperglycemic episodes, which result from insufficient insulin production. As the diabetes disease progresses, it requires an advance control of external insulin administration with an insulin pump. Given the importance of blood-glucose level prediction for the insulin therapy, there is a Blood-Glucose Level Prediction Challenge. This prediction is based on a post-mortem dataset, which include a number of signals related to the daily life of a diabetic patient. We propose replacing these post-mortem signals with an in-silico diabetic patient. For this purpose, we can use the SmartCGMS continuous glucose monitoring and controlling framework together with an FDA-accepted diabetic patient simulation. As a result, a competing researcher have the same conditions as a developer of a real-life insulin pump, connected to a real diabetic patient. When using SmartCGMS, simulated, prototyped and real devices can work together. This approach reduces the difference between laboratory and practical results, thus increasing the level of realism for the entire challenge. As a report on the current SmartCGMS state, we describe the previously unpublished features, which enable an improved glucose level prediction and/or control challenge

Název v anglickém jazyce

SmartCGMS as a Testbed for a Blood-Glucose Level Prediction and/or Control Challenge with (an FDA-Accepted) Diabetic Patient Simulation

Popis výsledku anglicky

Diabetic patient desires to avoid hypo- and hyperglycemic episodes, which result from insufficient insulin production. As the diabetes disease progresses, it requires an advance control of external insulin administration with an insulin pump. Given the importance of blood-glucose level prediction for the insulin therapy, there is a Blood-Glucose Level Prediction Challenge. This prediction is based on a post-mortem dataset, which include a number of signals related to the daily life of a diabetic patient. We propose replacing these post-mortem signals with an in-silico diabetic patient. For this purpose, we can use the SmartCGMS continuous glucose monitoring and controlling framework together with an FDA-accepted diabetic patient simulation. As a result, a competing researcher have the same conditions as a developer of a real-life insulin pump, connected to a real diabetic patient. When using SmartCGMS, simulated, prototyped and real devices can work together. This approach reduces the difference between laboratory and practical results, thus increasing the level of realism for the entire challenge. As a report on the current SmartCGMS state, we describe the previously unpublished features, which enable an improved glucose level prediction and/or control challenge

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>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

Procedia Computer Science 177

ISBN

—

ISSN

1877-0509

e-ISSN

—

Počet stran výsledku

9

Strana od-do

354-362

Název nakladatele

Elsevier

Místo vydání

—

Místo konání akce

Madeira, Portugalsko

Datum konání akce

2. 11. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—