Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state assessment. Reliable FHR signal can be obtained from an invasive direct fetal electrocardiogram (FECG), but this is limited to labour. Alternative abdominal (indirect) FECG signals can be recorded during pregnancy and labour. Quality, however, is much lower and the maternal heart and uterine contractions provide sources of interference. Here, we present ten twenty-minute pregnancy signals and 12 five-minute labour signals. Abdominal FECG and reference direct FECG were recorded simultaneously during labour. Reference pregnancy signal data came from an automated detector and were corrected by clinical experts. The resulting dataset exhibits a large variety of interferences and clinically significant FHR patterns. We thus provide the scientific community with access to bioelectrical fetal heart activity signals that may enable the development of new methods for FECG signals analysis, and may ultimately advance the use and accuracy of abdominal electrocardiography methods.

Łukasiewicz Research Network Institute of Medical Technology and Equipment 118 Roosevelt Str 41 800 Zabrze Poland

Silesian University of Technology Department of Cybernetics Nanotechnology and Data Processing 16 Akademicka Str 44 100 Gliwice Poland

VSB Technical University of Ostrava Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science 17 Listopadu 2172 15 Str 70800 Ostrava Czech Republic

Associated Dataset

doi: 10.1007/s11517-006-0054-0 PubMed

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Abdulhay E, et al. Non-Invasive Fetal Heart Rate Monitoring Techniques: Review Article. Biomedical Science and Engineering. 2014;2:53–67.

Wrobel J, Horoba K, Pander T, Jezewski J, Czabanski R. Improving the fetal heart rate signal interpretation by application of myriad filtering. Biocybern. Biomed. Eng. 2013;33:211–221.

Jezewski, J., Wrobel, J. Fetal monitoring with automated analysis of cardiotocogram: the KOMPOR System. Proc. 15th Ann. Int. Conf. IEEE Engineering in Medicine and Biology Society. San Diego, California USA, 28–31 October 1993, 638–639 (1993).

Jezewski J, Kupka T, Horoba K. Extraction of fetal heart rate signal as time event series from evenly sampled data acquired using Doppler ultrasound technique. IEEE Trans. Biomed. Eng. 2008;55:805–810. PubMed

Jezewski J, et al. Selected design issues of the medical cyber-physical system for telemonitoring pregnancy at home. Microprocess. Microsy. 2016;46:35–43.

Kupka, T., Jezewski, J., Matonia, A. & Horoba, K. Timing events in Doppler ultrasound signal of fetal heart activity, Proc. 26th Ann. Int. Conf. IEEE Engineering in Medicine and Biology Society. San Francisco, California USA, 1–5 September 2004, 337–340 (2004). PubMed

Signorini M, Magenes G, Cerutti S, Arduini D. Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings. IEEE Trans. Biomed. Eng. 2003;50:365–374. PubMed

Wrobel J, et al. Medical cyber-physical system for home telecare of high-risk pregnancy – design challenges and requirements. J. Med. Imag. Health. In. 2015;5:1295–1301.

Jongsma HW, van Oosterom A, Murray HG, van Geijn HP. Introduction to fetal electrocardiography. J. Perinat. Med. 1986;14:347–348.

Kahankova, R. et al. A review of signal processing techniques for non-invasive fetal electrocardiography. IEEE Rev. Biomed. Eng. 13, 51–73 (2019). PubMed

Hon E. Instrumentation of fetal heart rate and fetal electrocardiography. II. A vaginal electrode. Am. J. Obstet. Gynecol. 1963;86:772–778. PubMed

Agostinelli A, et al. Noninvasive Fetal Electrocardiography: An Overview of the Signal Electrophysiological Meaning, Recording Procedures, and Processing Techniques. Ann. Noninvas. Electro. 2015;20:303–313. PubMed PMC

Martinek R, et al. Non-invasive fetal monitoring: a maternal surface ECG electrode placement-based novel approach for optimization of adaptive filter control parameters using the LMS and RLS algorithms. Sensors. 2017;17:1154. PubMed PMC

Karvounis E, et al. A non-invasive methodology for fetal monitoring during pregnancy. Methods Inf. Med. 2010;49:238–253. PubMed

Kahankova R, et al. The influence of gestation age on the performance of adaptive algorithms used for fetal ECG signal extraction. Adv. Elect. Electr. Eng. 2017;15:491–501.

Joseph, J., Gini, J. R. & Ramachandran, K. I. Removal of BW and respiration noise in abdECG for fECG extraction. Proc. Int. Symp. on Signal Processing and Intelligent Recognition Systems (SIRS’2017). Thampi, S. M. et al., Eds., Advances in Signal Processing and Intelligent Recognition Systems, Manipal, India, 13–16 September 2017, Springer International Publishing AG 2018, 678, 3–14 (2017).

Fotiadou E, van Laar JOEH, Oei SG, Vullings R. Enhancement of low-quality fetal electrocardiogram based on time-sequenced adaptive filtering. Med. Biol. Eng. Comput. 2018;56:2313–2323. PubMed PMC

Behar J, Andreotti F, Zaunseder S, Oster J, Clifford GD. A practical guide to non-invasive foetal electrocardiogram extraction and analysis. Physiol. Meas. 2016;37:R1–R35. PubMed

Clifford G, Silva I, Behar J, Moody G. Non-invasive fetal ECG analysis. Physiol. Meas. 2014;35:1521–1536. PubMed PMC

Kotas M. Combined application of independent component analysis and projective filtering to fetal ECG extraction. Biocybern. Biomed. Eng. 2008;28:75–93.

Martinek R. et al. Adaptive signal processing techniques for extracting abdominal fetal electrocardiogram, Proc. 10th Int. Symp. on Communication Systems Networks and Digital Signal Processing, (CSNDSP). Prague, Czech Republic, 20–22 July 2016, (2016).

Sameni R, Clifford G. A review of fetal ECG signal processing issues and promising directions. Open Pacing Electrophysiol. Ther. J. 2010;3:4–20. PubMed PMC

Mousavian I, Shamsollahi MB, Fatemizadeh E. Noninvasive fetal ECG extraction using doubly constrained block-term decomposition. Math. Biosci. Eng. 2019;17:144–159. PubMed

Castillo E, et al. A clustering-based method for single-channel fetal heart rate monitoring. PLoS ONE. 2018;13(6):e0199308. PubMed PMC

Behar J, Oster J, Clifford GD. Non-invasive FECG extraction from a set of abdominal sensors. Comput. Cardiol. 2013;40:297–300.

Crowe J, Woolfson M, Hayes-Gill B, Peasgood W. Antenatal Assessment using the FECG obtained via Abdominal Electrodes. J. Perinat. Med. 1996;24:43–53. PubMed

Karvounis E, Tsipouras M, Fotiadis D, Naka K. An automated methodology for fetal heart rate extraction from the abdominal electrocardiogram. IEEE Trans. Inf. Technol. Biomed. 2007;11:628–638. PubMed

Gacek A, Matonia A, Jezewski J, Kupka T. Recognition of early symptoms of fetal distress with on-line analysis of bioelectrical signals from maternal abdomen. Biocybern. Biomed. Eng. 2007;27:207–216.

Jezewski J, Wrobel J, Horoba K. Comparison of Doppler ultrasound and direct electrocardiography acquisition techniques for quantification of fetal heart variability. IEEE Trans. Biomed. Eng. 2006;53:855–864. PubMed

Jezewski M, Czabanski R, Wrobel J, Horoba K. Analysis of extracted cardiotocographic signal features to improve automated prediction of fetal outcome. Biocybern. Biomed. Eng. 2010;30:29–47.

Jezewski M, Czabanski R, Horoba K, Leski J. Clustering with pairs of prototypes to support automated assessment of the fetal state. Appl. Artif. Intell. 2016;30:572–589.

Kotas M, Jezewski J, Horoba K, Matonia A. Application of spatio-temporal filtering to fetal electrocardiogram enhancement. Comput. Meth. Prog. Bio. 2011;104:1–9. PubMed

Martinek R, et al. Comparative effectiveness of ICA and PCA in extraction of fetal ECG from abdominal signals: towards non-invasive fetal monitoring. Front. Physiol. 2018;9:Article 648. PubMed PMC

Matonia, A., Jezewski, J., Horoba, K., Gacek, A. & Labaj, P. The maternal ECG suppression algorithm for efficient extraction of the fetal ECG from abdominal signal. Proc. 28th Ann. Int. Conf. of the IEEE Engineering in Medicine and Biology Society, New York, New York USA, 30 August–3 September 2006, 3106–3109 (2006). PubMed

Matonia, A., Jezewski, J., Kupka, T., Horoba, K. & Wrobel, J. Algorithm for recognition and suppression of interfering maternal electrocardiography. Proc. 3rd Int. Conf. on Computer Recognition Systems (KOSYR’2003), Milkow, Poland, 26–29 May 2003, 55–61. ISBN 83-911675-7-7 (2003).

Jezewski J, Matonia A, Kupka T, Roj D, Czabanski R. Determination of the fetal heart rate from abdominal signals: evaluation of beat-to-beat accuracy in relation to the direct fetal electrocardiogram. Biomed. Eng. 2012;57:383–394. PubMed

Kotas M, Jezewski J, Matonia A, Kupka T. Towards noise immune detection of fetal QRS complexes. Comput. Meth. Prog. Bio. 2010;97:241–256. PubMed

Matonia, A., Kupka, T., Jezewski, J. & Horoba, K. Evaluation of the QRS detection algorithms in relation to fetal heart rate estimation. Proc. 3rd European Medical & Biological Engineering Conference – IFMBE European Conference on Biomedical Engineering (EMBEC’05). 20-25 November 2005, Prague, Czech Republik, 11 (2005).

Taralunga, D. D., Ungureanu, G. M., Gussi, I., Strungaru, R. & Wolf, W. Fetal ECG extraction from abdominal signals: a review on suppression of fundamental power line interference component and its harmonics. Comput. Math. Method. M. Article ID 239060, 15 pages (2014). PubMed PMC

Matonia A, Jezewski J, Kupka T, Horoba K, Wrobel J. The influence of coincidence of fetal and maternal QRS complexes on fetal heart rate reliability. Med. Biol. Eng. Comput. 2006;44:393–403. PubMed

Wrobel J, et al. Pregnancy telemonitoring with smart control of algorithms for signal analysis. J. Med. Imag. Health In. 2015;5:1302–1310.

Graatsma E, Jacod B, van Egmond L, Mulder E, Visser G. Fetal electrocardiography: feasibility of long-term fetal heart rate recordings. Br. J. Obstet. Gynaecol. 2009;116:334–338. PubMed

Pieri J, et al. Compact long-term recorder for the transabdominal foetal and maternal electrocardiogram. Med. Biol. Eng. Comput. 2001;39:118–125. PubMed

Guerrero-Martinez J, Martinez-Sober M, Bataller-Mompean M, Magdaleno-Benedito J. New algorithm for fetal QRS detection in surface abdominal records. Comput. Cardiol. 2006;33:441–444.

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.

Marchon, N., Naik, G. & Pai K. R. Linear phase sharp transition BPF to detect noninvasive maternal and fetal heart rate. J. Healthc. Eng. Article ID 5485728, 14 pages, (2018). PubMed PMC

De Haan J, et al. Quantitative evaluation of fetal heart rate patterns I. Processing methods. Europ. J. Obstet. Gynec. 1971;3:95–102.

Yan H, et al. Invariant heart beat span versus variant heart beat intervals and its application to fetal ECG extraction. Biomed. Eng. Online. 2014;13:163. PubMed PMC

Almeida R, Goncalves H, Bernardes J, Rocha AP. Fetal QRS detection and heart rate estimation: a wavelet-based approach. Physiol. Meas. 2014;35:1723–1735. PubMed

Azavedo S, Longini R. Abdominal-lead fetal electrocardiographic R-wave enhancement for heart rate determination. IEEE Trans. Biomed. Eng. 1980;27:255–259. PubMed

Agostinelli A, et al. Noninvasive fetal electrocardiography Part I: Pan-Tompkins’ algorithm adaptation to fetal R-peak identification. The Open Biomedical Engineering Journal. 2017;11:17–24. PubMed PMC

Matonia A, 2020. Fetal electrocardiograms, direct and abdominal with reference heart beats annotations. figshare. PubMed DOI PMC

Matonia A, 2012. Abdominal and Direct Fetal ECG Database. PhysioNet. DOI

Jezewski, J. et al. A new approach to cardiotocographic fetal monitoring based on analysis of bioelectrical signals. 25th Int. Conf. of IEEE Engineering in Medicine and Biology Society, Cancum, Mexico, 17–21 September 2003, 3145–3149 (2003).

Horoba K, et al. Early predicting a risk of preterm labour by analysis of antepartum electrohysterograhic signals. Biocybern. Biomed. Eng. 2016;36:574–583.

Agostinelli A, et al. Noninvasive fetal electrocardiography Part II: Segmented-beat modulation method for signal denoising. The Open Biomedical Engineering Journal. 2017;11:25–35. PubMed PMC

Fuchs T. Values of T/QRS ratios measured during normal and post-term pregnancies. J. Perinat. Med. 2014;42:349–357. PubMed

Jaros R, Martinek R, Kahankova R. Non-adaptive methods for fetal ECG signal processing: a review and appraisal. Sensors. 2018;18(11):3648. PubMed PMC

De Moor B, De Gersem P, De Schutter B, Favoreel W. DAISY: A database for identification of systems. Journal A. 1997;38:4–5.

Goldberger AL, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:e215–e220. PubMed

Andreotti F, Behar J, Zaunseder S, Oster J, Clifford GD. An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms. Physiol. Meas. 2016;37:627–648. PubMed

Behar J, et al. An ECG model for simulating maternal-foetal activity mixtures on abdominal ECG recordings. Physiol. Meas. 2014;35:1537–1549. PubMed

Andreotti F, et al. Robust fetal ECG extraction and detection from abdominal leads. Physiol. Meas. 2014;35:1551–1567. PubMed

Christov I, Simova I, Abacherli R. Extraction of the fetal ECG in noninvasive recordings by signal decompositions. Physiol. Meas. 2014;35:1713–1721. PubMed

Da Poian G, Bernardini R, Rinaldo R. Separation and Analysis of Fetal-ECG Signals From Compressed Sensed Abdominal ECG Recordings. IEEE Trans. Biomed. Eng. 2016;63:1269–1279. PubMed

Khamene A, Negahdaripour S. A new method for the extraction of fetal ECG from the composite abdominal signal. IEEE Trans. Biomed. Eng. 2000;47:507–516. PubMed

Behar J, Oster J, Clifford GD. Combining and benchmarking methods of foetal ECG extraction without maternal or scalp electrode data. Physiol. Meas. 2014;35:1569–1589. PubMed

Vullings R, et al. A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings. Physiol. Meas. 2010;31:935–951. PubMed

Li, C., Fang, B., Li, H. & Wang, P. A novel method of FECG extraction combined self-correlation analysis with ICA. Proc. 8th IEEE Int. Conf. on Communication Software and Networks (ICCSN). Beijing, China 4–6 June 2016, 107–111 (2016).

Liu G, Luan Y. An adaptive integrated algorithm for noninvasive fetal ECG separation and noise reduction based on ICA-EEMD-WS. Med. Biol. Eng. Comput. 2015;53:1113–1127. PubMed

Kotas M. Projective Filtering for Fetal ECG extraction. Bull. Pol. Acad. Sci.Te. 2007;55:331–339.

Friesen G, et al. A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Trans. Biomed. Eng. 1990;37:85–98. PubMed

Pan J, Tompkins W. A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. 1985;32:230–236. PubMed

Silva I, et al. Noninvasive Fetal ECG: the PhysioNet/Computing in Cardiology Challenge 2013. Comput. Cardiol. 2013;40:149–152. PubMed PMC

Rodrigues R. Fetal beat detection in abdominal ECG recordings: global and time adaptive approaches. Physiol. Meas. 2014;35:1699–1711. PubMed

Lee K, Lee B. Sequential total variation denoising for the extraction of fetal ECG from single-channel maternal abdominal ECG. Sensors. 2016;16:1020. PubMed PMC

John RG, Ramachandran KI. Extraction of foetal ECG from abdominal ECG by nonlinear transformation and estimations. Comput. Meth. Prog. Bio. 2019;175:193–204. PubMed

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