AccScience Publishing / GTM / Online First / DOI: 10.36922/GTM025260052
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ORIGINAL RESEARCH ARTICLE

Models for non-invasive fetal electroencephalogram signal extraction during gestation

Eden Koresh1 ,  Ophir Oren1 ,  Offer Erez2,3,4* ,  Ali Nasirlou2 ,  Eilon Shany5 ,  Robert Clancy6 ,  Yaniv Zigel1 ,  Taeer Avnon7 ,  Allon Guez8
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1 Department of Biomedical Engineering, Faculty of Engineering, Ben Gurion University of the Negev, Beer Sheva, Israel
2 FetalEEG Inc., Penn Valley, Pennsylvania, United States of America
3 Department of Obstetrics and Gynecology, Soroka University Medical Center, Ben Gurion University of the Negev, Beer Sheva, Israel
4 Department of Obstetrics and Gynecology, School of Medicine, Wayne State University, Detroit, Michigan, United States of America
5 Department of Neonatology, Soroka University Medical Center, Ben Gurion University of the Negev, Beer Sheva, Israel
6 Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America
7 School of Medicine, Ben Gurion University of the Negev, Beer Sheva, Israel
8 Department of Electrical Engineering, College of Engineering, Drexel University, Philadelphia, Pennsylvania, United States of America
Global Translational Medicine, 025260052 https://doi.org/10.36922/GTM025260052
Received: 24 June 2025 | Revised: 31 October 2025 | Accepted: 4 November 2025 | Published online: 22 December 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

The functional development of the fetal brain is critical for long-term health, yet current diagnostic tools lack the capability to examine it effectively. This paper presents a non-invasive method for extracting fetal brain signals using abdominal recordings obtained before elective cesarean sections, with neonatal brain activity recorded post-delivery serving as a reference. The recorded abdominal signals were preprocessed using digital filters and separated into independent components using the blind source separation technique: Independent component analysis. These components were analyzed to identify potential fetal brain signals based on their similarity to postnatal brain activity and dissimilarity to maternal cardiac signals, which are the primary source of interference in abdominal recordings. Features related to time and frequency characteristics were extracted, and a feature selection was conducted to identify the most informative ones. Preliminary results using simulated data demonstrated effective signal separation, with some segments closely resembling postnatal brain activity in spectral features. Low-frequency bands showed the strongest potential for distinguishing fetal brain activity from maternal interference. This approach demonstrates a feasible pathway for non-invasive fetal brain monitoring with implications for early detection of neurological development issues.

Keywords
Fetal brain function
Neonatal electroencephalogram
Signal processing
Non-invasive monitoring
Independent component analysis
Frequency-domain analysis
Cesarean section
Funding
This research was supported by the Ministry of Innovation, Science and Technology, Israel (grant number: 0004750).
Conflict of interest
The authors declare no competing interests.
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Global Translational Medicine, Electronic ISSN: 2811-0021 Print ISSN: 3060-8600, Published by AccScience Publishing
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