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Brno University of Technology, Czech Republic

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Brno University of Technology, Czech Republic

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National Taiwan University of Science and Technology, Taiwan, Province of China

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Ankara University, Turkey

Janusz Jezewski
Institute of Medical Technology and Equipment, Poland

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VSB - Technical University of Ostrava, Czech Republic

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Academy of Sciences of the Czech Republic, Czech Republic

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University of Defence, Czech Republic

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Technical University of Radom, Poland

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Technical University of Kosice, Slovakia

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Hongik University, Korea

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Buryat State University, Russia

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Ton Duc Thang University, Vietnam

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Ca’ Foscari University of Venice, Italy

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University of New Haven, United States of America

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Ton Duc Thang University, Vietnam

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VSB - Technical University of Ostrava, Czech Republic

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Wroclaw University of Science and Technology, Poland

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The University of Edinburgh, United Kingdom

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Guanajuato University, Mexico

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Technical University of Cluj Napoca, Romania

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Posts and Telecommunications Institute of Technology, Ho Chi Minh City, Vietnam

Xingwang Li
Henan Polytechnic University, China

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Ton Duc Thang University, Vietnam

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University of Pardubice, Czech Republic

Neeta Pandey
Delhi Technological University, India

Huynh The Thien
Ho Chi Minh City University of Technology and Education, Vietnam

Mauro Tropea
DIMES Department of University of Calabria, Italy

Gaojian Huang
Henan Polytechnic University, China

Nguyen Quang Sang
Ho Chi Minh City University of Transport, Vietnam

Anh-Tu Le
Ho Chi Minh City University of Transport, Vietnam

Phu Tran Tin
Ton Duc Thang University, Vietnam


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Influence of gestation age on the performance of adaptive systems for fetal ECG extraction

Radana Kahankova, Janusz Jezewski, Jan Nedoma, Michal Jezewski, Marcel Fajkus, Aleksandra Kawala-Janik, He Wen, Radek Martinek

DOI: 10.15598/aeee.v15i3.2207


Abstract

The main aims of this paper are to study the influence of the Gestation Age (GA) on the quality of recorded abdominal ECG (aECG) signals and to evaluate the performance of the LMS and RLS adaptive signal processing algorithms in the extraction of the fetal ECG (fECG) signal component from such signals. This influence is quantified as a function of the Signal-to-Noise Ratio (SNR). Our research shows that these adaptive algorithms with optimized settings can successfully be applied to extract fECG signals from the maternal aECG signals as early as the 30th week of GA, hence addressing a limitation (37 weeks or labor) in commercially available monitoring systems. We demonstrate that before this gestational age, the SNR of the maternal aECG signal is too low for these adaptive algorithms to work effectively and produce satisfactory results.

Keywords


ECG extraction; fetal ElectroCardioGram (ECG); gestation age; LMS and RLS algorithms; non-invasive fetal monitoring.

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