System for adaptive extraction of non-invasive fetal electrocardiogram

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248313" target="_blank" >RIV/61989100:27240/21:10248313 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1568494621008620" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1568494621008620</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.asoc.2021.107940" target="_blank" >10.1016/j.asoc.2021.107940</a>

Jazyk výsledku

angličtina

Název v původním jazyce

System for adaptive extraction of non-invasive fetal electrocardiogram

Popis výsledku v původním jazyce

This study aimed to find the most suitable combination of adaptive and non-adaptive methods for extraction of non-invasive fetal electrocardiogram (NI-fECG) using signals recorded from the mother&apos;s abdomen. Among the nine methods considered, the combination of independent component analysis (ICA), fast transversal filter (FTF), and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) proved to be the most effective for the extraction of fECG from abdominal recordings. This combined method was suitable due to both being effective in extracting fECG and being less computationally complex. Further, so far, FTF and CEEMDAN methods have not been extensively tested for fECG extraction, and in particular, have not been examined as a hybrid method. The ICA-FTF-CEEMDAN hybrid algorithm was tested on two patient databases: Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations (FECGDARHA) and PhysioNet Challenge 2013. The evaluation of the accuracy of fQRS complexes detection was performed using the following parameters: accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and F1 score. The fetal heart rate (fHR) determination accuracy was evaluated using Bland-Altman plots and fHR traces. When testing on the FECGDARHA database, average values of ACC = 92.98%, SE = 95.33%, PPV = 96.4% and F1 = 95.86% for detection fQRS were achieved. The error in estimating the fHR was -1.02 +/- 7.02 (mu +/- 1.96 sigma) bpm. When testing on the Challenge 2013 database, average values of ACC = 78.47%, SE = 82.06%, PPV = 87.90% and F1 = 84.62% for fQRS detection were achieved, and the error in estimating the fHR was -6.62 +/- 10.33 (mu +/- 1.96 sigma) bpm. In addition, a non-invasive morphological analysis (ST analysis) was performed on the records from the FECGDARHA database, which was accurate in 7 of 12 records with values of mu &lt; 0.03 and values of +/- 1.96 sigma &lt; 0.04. (C) 2021 The Author(s). Published by Elsevier B.V.

Název v anglickém jazyce

System for adaptive extraction of non-invasive fetal electrocardiogram

Popis výsledku anglicky

This study aimed to find the most suitable combination of adaptive and non-adaptive methods for extraction of non-invasive fetal electrocardiogram (NI-fECG) using signals recorded from the mother&apos;s abdomen. Among the nine methods considered, the combination of independent component analysis (ICA), fast transversal filter (FTF), and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) proved to be the most effective for the extraction of fECG from abdominal recordings. This combined method was suitable due to both being effective in extracting fECG and being less computationally complex. Further, so far, FTF and CEEMDAN methods have not been extensively tested for fECG extraction, and in particular, have not been examined as a hybrid method. The ICA-FTF-CEEMDAN hybrid algorithm was tested on two patient databases: Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations (FECGDARHA) and PhysioNet Challenge 2013. The evaluation of the accuracy of fQRS complexes detection was performed using the following parameters: accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and F1 score. The fetal heart rate (fHR) determination accuracy was evaluated using Bland-Altman plots and fHR traces. When testing on the FECGDARHA database, average values of ACC = 92.98%, SE = 95.33%, PPV = 96.4% and F1 = 95.86% for detection fQRS were achieved. The error in estimating the fHR was -1.02 +/- 7.02 (mu +/- 1.96 sigma) bpm. When testing on the Challenge 2013 database, average values of ACC = 78.47%, SE = 82.06%, PPV = 87.90% and F1 = 84.62% for fQRS detection were achieved, and the error in estimating the fHR was -6.62 +/- 10.33 (mu +/- 1.96 sigma) bpm. In addition, a non-invasive morphological analysis (ST analysis) was performed on the records from the FECGDARHA database, which was accurate in 7 of 12 records with values of mu &lt; 0.03 and values of +/- 1.96 sigma &lt; 0.04. (C) 2021 The Author(s). Published by Elsevier B.V.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Centrum výzkumu pokročilých mechatronických systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Applied Soft Computing

ISSN

1568-4946

e-ISSN

—

Svazek periodika

113

Číslo periodika v rámci svazku

B

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

20

Strana od-do

—

Kód UT WoS článku

000724750600008

EID výsledku v databázi Scopus

—