The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms. However, there are many variants of the ICA methods and it is not clear which one is the most suitable for this task. The goal of this study is to test and objectively evaluate 11 variants of ICA methods combined with an adaptive fast transversal filter (FTF) for the purpose of extracting the NI-fECG. The methods were tested on two datasets, Labour dataset and Pregnancy dataset, which contained real records obtained during clinical practice. The efficiency of the methods was evaluated from the perspective of determining the accuracy of detection of QRS complexes through the parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). The best results were achieved with a combination of FastICA and FTF, which yielded mean values of ACC = 83.72%, SE = 92.13%, PPV = 90.16%, and F1 = 91.14%. Time of calculation was also taken into consideration in the methods. Although FastICA was ranked to be the sixth fastest with its mean computation time of 0.452 s, it had the best ratio of performance and speed. The combination of FastICA and adaptive FTF filter turned out to be very promising. In addition, such device would require signals acquired from the abdominal area only; no need to acquire reference signal from the mother's chest.

Department of Applied Mathematics Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava Ostrava Czechia

Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava Ostrava Czechia

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Sameni. A Review of Fetal ECG Signal Processing Issues and Promising Directions. The Open Pacing, Electrophysiology & Therapy Journal. 2010; doi: 10.2174/1876536X01003010004 PubMed DOI PMC

Gurve D, Krishnan S. Separation of Fetal-ECG From Single-Channel Abdominal ECG Using Activation Scaled Non-Negative Matrix Factorization. IEEE Journal of Biomedical and Health Informatics. 2020;24(3):669–680. doi: 10.1109/JBHI.2019.2920356 PubMed DOI

Giussani DA. The Fetal Brain Sparing Response to Hypoxia: Physiological Mechanisms: Fetal Brain Sparing. The Journal of Physiology. 2016;594(5):1215–1230. doi: 10.1113/JP271099 PubMed DOI PMC

Uzianbaeva L, Yan Y, Joshi T, Yin N, Hsu CD, Hernandez-Andrade E, et al.. Methods for Monitoring Risk of Hypoxic Damage in Fetal and Neonatal Brains: A Review. Fetal Diagnosis and Therapy. 2022;49(1-2):1–24. doi: 10.1159/000520987 PubMed DOI PMC

Abdulhay EW, Oweis RJ, Alhaddad AM, Sublaban FN, Radwan MA, Almasaeed HM. Non-Invasive Fetal Heart Rate Monitoring Techniques: Review Article. Biomedical Science and Engineering. 2014;2:53–67.

Cohen WR, Hayes-Gill B. Influence of Maternal Body Mass Index on Accuracy and Reliability of External Fetal Monitoring Techniques. Acta Obstetricia et Gynecologica Scandinavica. 2014;93(6):590–595. doi: 10.1111/aogs.12387 PubMed DOI

Spilka J, Chudacek V, Janku P, Hruban L, Bursa M, Huptych M, et al.. Analysis of Obstetricians’ Decision Making on CTG Recordings. Journal of Biomedical Informatics. 2014;51:72–79. doi: 10.1016/j.jbi.2014.04.010 PubMed DOI

Cohen WR, Ommani S, Hassan S, Mirza FG, Solomon M, Brown R, et al.. Accuracy and Reliability of Fetal Heart Rate Monitoring Using Maternal Abdominal Surface Electrodes: Maternal Surface Electrode Fetal Monitoring. Acta Obstetricia et Gynecologica Scandinavica. 2012;91(11):1306–1313. doi: 10.1111/j.1600-0412.2012.01533.x PubMed DOI

Luzietti R, Erkkola R, Hasbargen U, Mattsson LÅ, Thoulon JM, Rosen KG. European Community Multi-Center Trial “Fetal ECG Analysis During Labor”: ST plus CTG Analysis. Journal of Perinatal Medicine. 1999;27(6). doi: 10.1515/JPM.1999.058 PubMed DOI

Cuneo BF, Strasburger JF, Wakai RT. The Natural History of Fetal Long QT Syndrome. Journal of Electrocardiology. 2016;49(6):807–813. doi: 10.1016/j.jelectrocard.2016.07.023 PubMed DOI PMC

Mitchell JL, Cuneo BF, Etheridge SP, Horigome H, Weng HY, Benson DW. Fetal Heart Rate Predictors of Long QT Syndrome. Circulation. 2012;126(23):2688–2695. doi: 10.1161/CIRCULATIONAHA.112.114132 PubMed DOI

Widatalla N, Kasahara Y, Kimura Y, Khandoker A. Model Based Estimation of QT Intervals in Non-Invasive Fetal ECG Signals. PLOS ONE. 2020;15(5):e0232769. doi: 10.1371/journal.pone.0232769 PubMed DOI PMC

Kahankova R, Barnova K, Jaros R, Pavlicek J, Snasel V, Martinek R. Pregnancy in the Time of COVID-19: Towards Fetal Monitoring 4.0. BMC Pregnancy and Childbirth. 2023;23(1):33. doi: 10.1186/s12884-023-05349-3 PubMed DOI PMC

Mhajna M, Schwartz N, Levit-Rosen L, Warsof S, Lipschuetz M, Jakobs M, et al.. Wireless, Remote Solution for Home Fetal and Maternal Heart Rate Monitoring. American Journal of Obstetrics & Gynecology MFM. 2020;2(2):100101. doi: 10.1016/j.ajogmf.2020.100101 PubMed DOI

Jaros R, Martinek R, Kahankova R, Koziorek J. Novel Hybrid Extraction Systems for Fetal Heart Rate Variability Monitoring Based on Non-Invasive Fetal Electrocardiogram. IEEE Access. 2019;7:131758–131784. doi: 10.1109/ACCESS.2019.2933717 DOI

Barnova K, Martinek R, Jaros R, Kahankova R, Matonia A, Jezewski M, et al.. A Novel Algorithm Based on Ensemble Empirical Mode Decomposition for Non-Invasive Fetal ECG Extraction. PLOS ONE. 2021;16(8):e0256154. doi: 10.1371/journal.pone.0256154 PubMed DOI PMC

Yuan L, Zhou Z, Yuan Y, Wu S. An Improved FastICA Method for Fetal ECG Extraction. Computational and Mathematical Methods in Medicine. 2018;2018:1–7. doi: 10.1155/2018/7061456 PubMed DOI PMC

Al-Sheikh B, Salman MS, Eleyan A, Alboon S. Non-Invasive Fetal ECG Extraction Using Discrete Wavelet Transform Recursive Inverse Adaptive Algorithm. Technology and Health Care. 2020;28(5):507–520. doi: 10.3233/THC-191948 PubMed DOI

He P, Chen X. A Method for Extracting Fetal ECG Based on EMD-NMF Single Channel Blind Source Separation Algorithm. Technology and Health Care. 2015;24(s1):S17–S26. doi: 10.3233/THC-151044 PubMed DOI

Ghobadi Azbari P, Abdolghaffar M, Mohaqeqi S, Pooyan M, Ahmadian A, Ghanbarzadeh Gashti N. A Novel Approach to the Extraction of Fetal Electrocardiogram Based on Empirical Mode Decomposition and Correlation Analysis. Australasian Physical & Engineering Sciences in Medicine. 2017;40(3):565–574. doi: 10.1007/s13246-017-0560-4 PubMed DOI

Martens SMM, Rabotti C, Mischi M, Sluijter RJ. A Robust Fetal ECG Detection Method for Abdominal Recordings. Physiological Measurement. 2007;28(4):373–388. doi: 10.1088/0967-3334/28/4/004 PubMed DOI

Ramli DA, Shiong YH, Hassan N. Blind Source Separation (BSS) of Mixed Maternal and Fetal Electrocardiogram (ECG) Signal: A Comparative Study. Procedia Computer Science. 2020;176:582–591. doi: 10.1016/j.procs.2020.08.060 DOI

Sevim Y, Atasoy A. Performance Evaluation of Nonparametric ICA Algorithm for Fetal ECG Extraction. Turkish Journal of Electrical Engineering & Computer Sciences. 2011;19(4):657–666.

Sheikh M, Marai M, Alhutaish R. Online Detection and Extraction of FECG Signals Using ICA: A Comparative Study. Journal of Engineering Research and Reports. 2020; p. 10–18. doi: 10.9734/jerr/2020/v15i217140 DOI

Rahmati AK, Setarehdan SK, Araabi BN. A PCA/ICA Based Fetal ECG Extraction from Mother Abdominal Recordings by Means of a Novel Data-Driven Approach to Fetal ECG Quality Assessment. Journal of biomedical physics & engineering. 2017;7(1):37. PubMed PMC

Sameni R, Jutten C, Shamsollahi MB. Multichannel Electrocardiogram Decomposition Using Periodic Component Analysis. IEEE Transactions on Biomedical Engineering. 2008;55(8):1935–1940. doi: 10.1109/TBME.2008.919714 PubMed DOI

Hyvärinen A, Oja E. Independent Component Analysis: Algorithms and Applications. Neural Networks. 2000;13(4-5):411–430. doi: 10.1016/S0893-6080(00)00026-5 PubMed DOI

Najafabadi FS, Zahedi E, Mohd Ali MA. Fetal Heart Rate Monitoring Based on Independent Component Analysis. Computers in Biology and Medicine. 2006;36(3):241–252. doi: 10.1016/j.compbiomed.2004.11.004 PubMed DOI

Barbati G, Porcaro C, Zappasodi F, Rossini PM, Tecchio F. Optimization of an Independent Component Analysis Approach for Artifact Identification and Removal in Magnetoencephalographic Signals. Clinical Neurophysiology. 2004;115(5):1220–1232. doi: 10.1016/j.clinph.2003.12.015 PubMed DOI

Choi S, Cichocki A, Amari SI. [No Title Found]. The Journal of VLSI Signal Processing. 2000;26(1/2):25–38. doi: 10.1023/A:1008135131269 DOI

Langlois D, Chartier S, Gosselin D. An Introduction to Independent Component Analysis: InfoMax and FastICA Algorithms. Tutorials in Quantitative Methods for Psychology. 2010;6(1):31–38. doi: 10.20982/tqmp.06.1.p031 DOI

Yang J, Gao X, Zhang D, Yang Jy. Kernel ICA: An Alternative Formulation and Its Application to Face Recognition. Pattern Recognition. 2005;38(10):1784–1787. doi: 10.1016/j.patcog.2005.01.023 DOI

Horigome H, Ishikawa Y, Shiono J, Iwamoto M, Sumitomo N, Yoshinaga M. Detection of Extra Components of T Wave by Independent Component Analysis in Congenital Long-QT Syndrome. Circulation: Arrhythmia and Electrophysiology. 2011;4(4):456–464. PubMed

Yao WP, Zhao JC, Zheng ZZ, Liu TB, Liu HX, Wang J. Fetal Electrocardiogram Extraction Based on Modified Robust Independent Component Analysis. Advanced Materials Research. 2013;749:250–253. doi: 10.4028/www.scientific.net/AMR.749.250 DOI

Albera L, Kachenoura A, Comon P, Karfoul A, Wendling F, Senhadji L, et al.. ICA-Based EEG Denoising: A Comparative Analysis of Fifteen Methods. Bulletin of the Polish Academy of Sciences: Technical Sciences. 2012;60(3):407–418. doi: 10.2478/v10175-012-0052-3 DOI

Turnip A. Comparison of ICA-Based JADE and SOBI Methods EOG Artifacts Removal. Journal of Medical and Bioengineering. 2015;4(6). doi: 10.12720/jomb.4.6.436-440 DOI

Dechene DJ. Fast Transversal Recursive Least-Squares (FT-RLS) Algorithm. In: IEEE Trans Signal Proc. Citeseer; 2007. p. 1–4.

Matonia A, Jezewski J, Kupka T, Jezewski M, Horoba K, Wrobel J, et al.. Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeat Annotations. Scientific Data. 2020;7(1):200. doi: 10.1038/s41597-020-0538-z PubMed DOI PMC

Billeci L, Varanini M. A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads. Sensors. 2017;17(5):1135. doi: 10.3390/s17051135 PubMed DOI PMC

Ghaffari A, Golbayani H, Ghasemi M. A New Mathematical Based QRS Detector Using Continuous Wavelet Transform. Computers & Electrical Engineering. 2008;34(2):81–91. doi: 10.1016/j.compeleceng.2007.10.005 DOI

Cheng L, Carlson ET, Vairavan S, Xu M. Fetal Heart Rate Extraction from Maternal Abdominal ECG Recordings. Google Patents. 2020;.

Kahankova R, Mikolasova M, Martinek R. Optimization of Adaptive Filter Control Parameters for Non-Invasive Fetal Electrocardiogram Extraction. PLOS ONE. 2022;17(4):e0266807. doi: 10.1371/journal.pone.0266807 PubMed DOI PMC

Kong L, Mirjalili S, Snasel V, Pan JS, Raj A, Kahankova RV, et al.. Analysis on Population-Based Algorithm Optimized Filter for Non-Invasive fECG Extraction. Applied Soft Computing. 2023;142:110323. doi: 10.1016/j.asoc.2023.110323 DOI

Rooijakkers MJ, Song S, Rabotti C, Oei SG, Bergmans JWM, Cantatore E, et al.. Influence of Electrode Placement on Signal Quality for Ambulatory Pregnancy Monitoring. Computational and Mathematical Methods in Medicine. 2014;2014:1–12. doi: 10.1155/2014/960980 PubMed DOI PMC

Huhn EA, Müller MI, Meyer AH, Manegold-Brauer G, Holzgreve W, Hoesli I, et al.. Quality Predictors of Abdominal Fetal Electrocardiography Recording in Antenatal Ambulatory and Bedside Settings. Fetal Diagnosis and Therapy. 2017;41(4):283–292. doi: 10.1159/000448946 PubMed DOI

Peters M, Crowe J, Pieri JF, Quartero H, Hayes-Gill B, James D, et al.. Monitoring the Fetal Heart Non-Invasively: A Review of Methods. Journal of Perinatal Medicine. 2001;29(5). doi: 10.1515/JPM.2001.057 PubMed DOI

Liu B, Thilaganathan B, Bhide A. Effectiveness of Ambulatory Non-invasive Fetal Electrocardiography: Impact of Maternal and Fetal Characteristics. Acta Obstetricia et Gynecologica Scandinavica. 2023;102(5):577–584. doi: 10.1111/aogs.14543 PubMed DOI PMC

Kahankova R, Jezewski J, Nedoma J, Jezewski M, Fajkus M, Kawala-Janik A, et al.. Influence of Gestation Age on the Performance of Adaptive Systems for Fetal ECG Extraction. Advances in Electrical and Electronic Engineering. 2017;15(3):491–501. doi: 10.15598/aeee.v15i3.2207 DOI

Himberg J, Hyvärinen A, Esposito F. Validating the Independent Components of Neuroimaging Time Series via Clustering and Visualization. NeuroImage. 2004;22(3):1214–1222. doi: 10.1016/j.neuroimage.2004.03.027 PubMed DOI

Pani D, Sulas E, Urru M, Sameni R, Raffo L, Tumbarello R. NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research; 2020. PubMed PMC

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al.. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation. 2000;101(23). doi: 10.1161/01.CIR.101.23.e215 PubMed DOI