Fetal ECG Signal Processing by Different ICA-based Algorithms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10245424" target="_blank" >RIV/61989100:27240/19:10245424 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9069725" target="_blank" >https://ieeexplore.ieee.org/document/9069725</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISAECT47714.2019.9069725" target="_blank" >10.1109/ISAECT47714.2019.9069725</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fetal ECG Signal Processing by Different ICA-based Algorithms

Popis výsledku v původním jazyce

This article deals with fetal electrocardiography (fECG) processing using independent component analysis (ICA). Testing is performed on 7 synthetic recordings with a different level of signal-to-noise ratio (SNR) and the evaluation is performed on calculation of improvement SNR and root mean square error (RMSE). The experiment was based on testing multiple algorithms based on the ICA method, such as the algorithm based on kurtosis value, the algorithm based on negentropy value and the algorithm called kurtosis maximization ICA. The results showed that all ICA-based algorithms a lot improve SNR and have a low value of RMSE, which indicates that signals after filtration are almost similar to the reference signals. All three ICA-based algorithms could be used for fECG extraction, but the lowest accuracy was achieved by the algorithm called kurtosis maximization ICA. (C) 2019 IEEE.

Název v anglickém jazyce

Fetal ECG Signal Processing by Different ICA-based Algorithms

Popis výsledku anglicky

This article deals with fetal electrocardiography (fECG) processing using independent component analysis (ICA). Testing is performed on 7 synthetic recordings with a different level of signal-to-noise ratio (SNR) and the evaluation is performed on calculation of improvement SNR and root mean square error (RMSE). The experiment was based on testing multiple algorithms based on the ICA method, such as the algorithm based on kurtosis value, the algorithm based on negentropy value and the algorithm called kurtosis maximization ICA. The results showed that all ICA-based algorithms a lot improve SNR and have a low value of RMSE, which indicates that signals after filtration are almost similar to the reference signals. All three ICA-based algorithms could be used for fECG extraction, but the lowest accuracy was achieved by the algorithm called kurtosis maximization ICA. (C) 2019 IEEE.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

2019 International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2019

ISBN

978-1-72813-729-2

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

—

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Řím

Datum konání akce

27. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000569987700054