Non-adaptive methods of fetal ecg signal processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238286" target="_blank" >RIV/61989100:27240/17:10238286 - isvavai.cz</a>

Výsledek na webu

<a href="http://advances.vsb.cz/index.php/AEEE/article/view/2196" target="_blank" >http://advances.vsb.cz/index.php/AEEE/article/view/2196</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15598/aeee.v15i3.2196" target="_blank" >10.15598/aeee.v15i3.2196</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Non-adaptive methods of fetal ecg signal processing

Popis výsledku v původním jazyce

Abdominal fetal ElectroCardioGrams (fECGs) carry a wealth of information about the fetus including fetal Heart Rate (fHR) and signal morphology during different stages of pregnancy. Here we report our results on the implementation and evaluation of two non-adaptive signal processing methods suitable for fECG signal extraction, namely: the Independent Component Analysis (ICA) and the Principal Component Analysis (PCA) Methods. We used the fetal heart rate extracted from fECG signals (in Beats Per Minute - BPM) and Signal-to-Noise Ratio (SNR) as effective performance evaluation metrics for our applied methods. Our findings demonstrated that given adequate SNR, these methods produced excellent results in accurate determination of fHR. Furthermore, we found out that compared to the PCA Method, the ICA Method produces a lower variance in the detection of the fHR. © 2017 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING.

Název v anglickém jazyce

Non-adaptive methods of fetal ecg signal processing

Popis výsledku anglicky

Abdominal fetal ElectroCardioGrams (fECGs) carry a wealth of information about the fetus including fetal Heart Rate (fHR) and signal morphology during different stages of pregnancy. Here we report our results on the implementation and evaluation of two non-adaptive signal processing methods suitable for fECG signal extraction, namely: the Independent Component Analysis (ICA) and the Principal Component Analysis (PCA) Methods. We used the fetal heart rate extracted from fECG signals (in Beats Per Minute - BPM) and Signal-to-Noise Ratio (SNR) as effective performance evaluation metrics for our applied methods. Our findings demonstrated that given adequate SNR, these methods produced excellent results in accurate determination of fHR. Furthermore, we found out that compared to the PCA Method, the ICA Method produces a lower variance in the detection of the fHR. © 2017 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Advances in Electrical and Electronic Engineering

ISSN

1336-1376

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

476-490

Kód UT WoS článku

000424330700012

EID výsledku v databázi Scopus

2-s2.0-85030541103