Direct Fetal Electrocardiogram Research Articles

Elicitation of fetal ECG from abdominal recordings using Blind Source Separation techniques and Robust Set Membership Affine Projection algorithm for signal quality enhancement

Background:The utilization of non-invasive techniques for fetal cardiac health surveillance is pivotal in evaluating fetal well-being throughout the gestational period. This process requires clean and interpretable fetal Electrocardiogram (fECG) signals. Method:The proposed work is the novel framework for the elicitation of fECG signals from abdominal ECG (aECG) recordings of the pregnant mother. The comprehensive approach encompasses pre-processing of the raw ECG signal, Blind Source Separation techniques (BSS), Decomposition techniques like Empirical Mode Decomposition (EMD), and its variants like Ensemble Empirical Mode Decomposition (EEMD), and Complete Ensemble Empirical Mode Decomposition with Additive Noise (CEEMDAN). The Robust Set Membership Affine Projection (RSMAP) Algorithm is deployed for the enhancement of the obtained fECG signal. Result:The results show significant improvements in the elicited fECG signal with a maximum Signal Noise Ratio (SNR) of 31.72 dB and correlation coefficient = 0.899, Maximum Heart Rate(MHR) obtained in the range of 108–142 bpm for all the records of abdominal ECG signals. The statistical test gave a p-value of 0.21 accepting the null hypothesis. The Abdominal and Direct Fetal Electrocardiogram Database (ABDFECGDB) from PhysioNet has been used for this analysis. Conclusion:The proposed framework demonstrates a robust and effective method for the elicitation and enhancement of fECG signals from the abdominal recordings.

Measuring fractal dynamics of FECG signals to determine the complexity of fetal heart rate

In this research, we study the fetal heart rate from abdominal signals using multi-fractal spectra and fractal analysis. We use the Abdominal and Direct Fetal Electrocardiogram Database contains multichannel fetal electrocardiogram (FECG) recordings obtained from 5 different women in labor, between 38 and 41 weeks of gestation. We apply autocorrelation or power spectral densities (PSD) analysis on these five FECG recordings to estimate the exponent from realizations of these processes and to find out if the signal of interest exhibits a power-law PSD. We perform multi-fractal analysis to discover whether some type of power-law scaling exists for various statistical moments at different scales of these FECG signals. We plot the multi-fractal spectra of this database to compare the width of the scaling exponent for each spectrum. A quantitative analysis commonly known as the Fractal Dimension (FD) using the Higuchi algorithm has been carried out to illustrate the fractal complexity of input signals. Our finding shows that the fractal geometry can be used as a mathematical model and computational framework to further analysis and classification of clinical database. Moreover, it can be considered as a framework to compare the complexity of FECG signals and a useful tool to differentiate between their patterns.

Fetal Heart Rate Extraction using NLMS Algorithm

This project develops a fetal heart rate (FHR) extraction application to analyze the fetus activity in the mother uterus. Several methods are available that can be used to detect FHR such as using the fetal electrocardiogram (FECG) that generated by fetus’ heart. Extracting FECG signals is considered a major challenge while the fetus is inside the mother uterus. Normalized Least Mean Square (NLMS) algorithm is one of adaptive filters that is chosen as adaptive filter to get FECG. Pan Tompkins algorithm is used for tracking R-peaks of heartbeat pulses of FECG signal. After detecting the RR interval a formula is used to calculate the bpm (heartbeat per minute) of FECG. Abdominal and direct FECG (ADFECG) database will be used to evaluate the implemented techniques as it has reference signal. At the end of research, calculated FHR is varied from 125.4 bpm to 130.3 bpm. When comparison is done between abdominal ECG (AECG) and direct FECG (DFECG), the error of FHR is 0.1%. The accuracy of R-peaks extraction is 100% where all R-peaks are detected by implemented techniques. MATLAB is used for signal simulations. This system will have ability to interpret the non-invasive FECG (NIFECG) database and compute its FHR.

Dynamic thresholding based efficient QRS complex detection with low computational overhead

QRS-complex detection is a primitive step in the detection of cardiac disorder using electrocardiogram (ECG). Abnormal and varying peaks, baseline wander and other noise are the main challenges in accurate QRS-complex detection. In this paper, A window-based FIR filter is used to eliminate the high-frequency noise. Next, the ECG is enhanced to the power third after multiplication followed by normalization and moving average process to retain dynamic QRS-complex. Then baseline and root mean square (RMS) value of first three seconds of the signal are used for initial thresholding, later dynamic thresholding process was utilized to update the threshold value after the detection of four R-peaks. The threshold value was automatically updated using the previous threshold value, R-peak amplitude, RR-interval, and RR-intervals means. Kurtosis coefficient computation is used for discarding prominent T-wave and further this technique located the QRS-complex accurately in the raw ECG signal. The proposed method was applied to Massachusetts Institute of Technology-Beth Israel Hospital Arrhythmia Database (MIT-BIH AD), Fantasia Database (FTD), European ST-T Database (ESTD), MIT-BIH Noise Stress Test Database (NSTD), and Direct Fetal ECG Database (FTD) for its evaluation and validation. The overall sensitivity rate of 99.70% and positive predictivity rate of 99.69% have been achieved. The proposed method is based on dynamic thresholding and simple decision rules, which makes this method computationally efficient. Wide validation over five different databases proves the robustness of this method.

Non-Invasive Fetal Electrocardiogram Extraction Based on Novel Hybrid Method for Intrapartum ST Segment Analysis

This study focuses on non-invasive fetal electrocardiogram extraction based on a novel hybrid method, which combines the advantages of non-adaptive and adaptive approaches for non-invasive fetal electrocardiogram morphological analysis. Besides estimating fetal heart rate, which is the main parameter used in the clinical practice, this study provides non-invasive ST segment analysis on data from Abdominal and Direct Fetal Electrocardiogram Database consisting of simultaneous traditional - gold standard invasive fetal scalp electrode and non-invasive fetal electrocardiogram recorded during delivery. This innovative approach utilizing the combination of independent component analysis and recursive least squares algorithms has the potential to extract valuable information from non-invasive fetal electrocardiogram in order to identify eventual sign of fetal distress. This was a prospective observational study of non-invasive fetal electrocardiogram, using 4 abdominally sited electrodes, against the traditional fetal scalp electrode on 8 patients. In terms of fetal heart rate estimation, the accuracy was high for all 8 tested patients with average value equaled 0.20 beats per minute and average value of 1.96 standard deviation equaled 5.80 beats per minute. In 7 patients, it was possible to perform the ST segment analysis with high accuracy in determining T/QRS in comparison with the reference fetal scalp electrode signal with average values and 1.96 standard deviation equaled 0.008 and 0.031 respectively. This study thus demonstrates that ST segment analysis is feasible using non-invasive fECG using the proposed hybrid method.

New Method for Beat-to-Beat Fetal Heart Rate Measurement Using Doppler Ultrasound Signal.

The most commonly used method of fetal monitoring is based on heart activity analysis. Computer-aided fetal monitoring system enables extraction of clinically important information hidden for visual interpretation—the instantaneous fetal heart rate (FHR) variability. Today’s fetal monitors are based on monitoring of mechanical activity of the fetal heart by means of Doppler ultrasound technique. The FHR is determined using autocorrelation methods, and thus it has a form of evenly spaced—every 250 ms—instantaneous measurements, where some of which are incorrect or duplicate. The parameters describing a beat-to-beat FHR variability calculated from such a signal show significant errors. The aim of our research was to develop new analysis methods that will both improve an accuracy of the FHR determination and provide FHR representation as time series of events. The study was carried out on simultaneously recorded (during labor) Doppler ultrasound signal and the reference direct fetal electrocardiogram Two subranges of Doppler bandwidths were separated to describe heart wall movements and valve motions. After reduction of signal complexity by determining the Doppler ultrasound envelope, the signal was analyzed to determine the FHR. The autocorrelation method supported by a trapezoidal prediction function was used. In the final stage, two different methods were developed to provide signal representation as time series of events: the first using correction of duplicate measurements and the second based on segmentation of instantaneous periodicity measurements. Thus, it ensured the mean heart interval measurement error of only 1.35 ms. In a case of beat-to-beat variability assessment the errors ranged from −1.9% to −10.1%. Comparing the obtained values to other published results clearly confirms that the new methods provides a higher accuracy of an interval measurement and a better reliability of the FHR variability estimation.

Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

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.

Blind extraction of fetal and maternal components from the abdominal electrocardiogram: An ICA implementation for low-dimensional recordings

This work studied Space-Time ICA (ST-ICA) on the separation of fetal and maternal ECGs from low-dimensional abdominal recordings. ST-ICA was implemented by combining the Method of Delays with FastICA and an automatic classifier and applied to the “Abdominal and Direct Fetal Electrocardiogram Database” in Physionet. Next, 24 indexes qualified the FECGs retrieved by using 4, 3, 2 channels and combinations of them (e.g., channels 1–3–4 or channels 2–4) with different configurations of FastICA (e.g., deflation and pow3). Results in five subjects indicate that, while the traditional implementation of FastICA only separated low quality FECGs in two subjects, ST-FastICA is more likely to consistently separate high quality FECGs in all subjects (even though the fetal and maternal QRS complexes were overlapping), this by using four channels, in the symmetric mode, independently on the nonlinearity. Results when using 3 and 2 channels also indicated that ST-FastICA is suitable for the separation of fetal and maternal ECGs, although the quality of the FECG extracted depended on the combination given by the channels used and the configurations of FastICA. Finally, when calculating RR intervals and fetal heart rate, ST-ICA (with 4 channels) showed no statistical differences with the Varanini et al. algorithm [1], one of the top-performing entries in the CinC13 Challenge. These preliminary results indicate that the temporal dynamics and the spatial information used by ST-FastICA make it possible for it to achieve a robust separation of ECGs in low-dimensional recordings where the traditional implementation of FastICA is more likely to fail.

An empirical sequence to extract fetal electrocardiogram using the Kernel and wavelet optimization

Fetal electrocardiogram (ECG) monitoring from the mother’s abdomen during pregnancy provides electrophysiological statistics of fetus heart. To separate fetal ECG from mother ECG is a signal separation technique that has the potential to give blind source information. In this paper, an empirical sequence of Kernel Independent Component Analysis (KICA) and Dual-Tree Complex Wavelet Transform (DTCWT) is implemented for efficient ECGs separation and post enhancement of extracted fetal ECG. The kernel approach provides a non-linear transformation and works in building contrast function based on mutual information. Further to remove unwanted disturbances, shift-invariant DTCWT is used to reconstruct filtered extracted fetal ECG. The proposed work is validated on Abdominal and Direct Fetal ECG Database (ADFECGDB) from the physionet. The proposed method also compares the accuracy and running time by implementing the FastICA method on the same dataset simultaneously.

Optimization of RLS Algorithm for Hybrid Method ICA-RLS

This paper deals with a design and implementation of a new approach to the extraction of fetal electrocardiography (fECG) signal by hybrid method combining independent component analysis (ICA) and adaptive algorithm based on recursive optimal adaptation (Recursive Least Square, RLS). The abdominal and direct fetal electrocardiogram database (ADFECGDB) was selected for the validation based on estimation of detection accuracy (ACC) relative to the reference signal recorded by means of fetal scalp electrode. The paper provides the tests of the RLS-based filter order setting in the range of 2 to 100 as well as optimization of the input channel combination to achieve the most accurate detection. In total, 11 electrode combinations were created out of 4 abdominal channels, and tested as the inputs of the ICA-RLS hybrid method. The results show that the method is very promising. The highest score was achieved for recording r0l ACC = 99.228 % with combination of input channels 1, 2, and 3 along with the RLS algorithm filter order 4.

Automatic T-Wave Alternans Identification in Indirect and Direct Fetal Electrocardiography.

Fetal T-wave alternans (TWA) is a still littleknown marker for severe fetus-heart instabilities and may be related to some currently unjustified fetal deaths. Automatically detecting TWA on direct fetal electrocardiograms (DFECG) means possibility of providing fetuses the right treatment during delivery. Instead, automatically identifying TWA on indirect fetal electrocardiograms (IFECG) means possibility of providing fetuses the right treatment even during pregnancy, when taking actions for outcome improvement is still possible. Moreover, TWA identification from IFECG is noninvasive, and thus safe for both fetuses and mothers. The aim of this work was testing the heart-rate adaptive match filter (HRAMF) for automatic TWA identification in IFECG and comparing HRAMF performance in IFECG against DFECG. To this aim, simultaneously recorded DFECG and IFECG tracings from 5 healthy fetuses were used ("Abdominal and Direct Fetal Electrocardiogram Database" from Physionet). TWA measurements (frequency, mean amplitude, maximum amplitude, and amplitude standard deviation) in IFECG (1.09±0.04 Hz, 11±5 μV, 21±12 μV and 7±3 μV) were of the same order of magnitude of those in DFECG (1.07±0.02 Hz, 9±2 μV, 30±11 μV and 6±2 μV). Moreover, a direct correlation (ñ) was found between maximum TWA and fetal heart rate (IFECG: ρ=0.999; P=0.022; DEFEG: ρ=0.642; P=0.243). Thus, HRAMF was able to detect TWA from IFECG as well as from DFECG.

Comparative Effectiveness of ICA and PCA in Extraction of Fetal ECG From Abdominal Signals: Toward Non-invasive Fetal Monitoring.

Non-adaptive signal processing methods have been successfully applied to extract fetal electrocardiograms (fECGs) from maternal abdominal electrocardiograms (aECGs); and initial tests to evaluate the efficacy of these methods have been carried out by using synthetic data. Nevertheless, performance evaluation of such methods using real data is a much more challenging task and has neither been fully undertaken nor reported in the literature. Therefore, in this investigation, we aimed to compare the effectiveness of two popular non-adaptive methods (the ICA and PCA) to explore the non-invasive (NI) extraction (separation) of fECGs, also known as NI-fECGs from aECGs. The performance of these well-known methods was enhanced by an adaptive algorithm, compensating amplitude difference and time shift between the estimated components. We used real signals compiled in 12 recordings (real01–real12). Five of the recordings were from the publicly available database (PhysioNet-Abdominal and Direct Fetal Electrocardiogram Database), which included data recorded by multiple abdominal electrodes. Seven more recordings were acquired by measurements performed at the Institute of Medical Technology and Equipment, Zabrze, Poland. Therefore, in total we used 60 min of data (i.e., around 88,000 R waves) for our experiments. This dataset covers different gestational ages, fetal positions, fetal positions, maternal body mass indices (BMI), etc. Such a unique heterogeneous dataset of sufficient length combining continuous Fetal Scalp Electrode (FSE) acquired and abdominal ECG recordings allows for robust testing of the applied ICA and PCA methods. The performance of these signal separation methods was then comprehensively evaluated by comparing the fetal Heart Rate (fHR) values determined from the extracted fECGs with those calculated from the fECG signals recorded directly by means of a reference FSE. Additionally, we tested the possibility of non-invasive ST analysis (NI-STAN) by determining the T/QRS ratio. Our results demonstrated that even though these advanced signal processing methods are suitable for the non-invasive estimation and monitoring of the fHR information from maternal aECG signals, their utility for further morphological analysis of the extracted fECG signals remains questionable and warrants further work.

Noninvasive Fetal Electrocardiography Part I: Pan-Tompkins' Algorithm Adaptation to Fetal R-peak Identification.

Background:Indirect fetal electrocardiography is preferable to direct fetal electrocardiography because of being noninvasive and is applicable also during the end of pregnancy, besides labor. Still, the former is strongly affected by noise so that even R-peak detection (which is essential for fetal heart-rate evaluations and subsequent processing procedures) is challenging. Some fetal studies have applied the Pan-Tompkins’ algorithm that, however, was originally designed for adult applications. Thus, this work evaluated the Pan-Tompkins’ algorithm suitability for fetal applications, and proposed fetal adjustments and optimizations to improve it. Method: Both Pan-Tompkins’ algorithm and its improved version were applied to the “Abdominal and Direct Fetal Electrocardiogram Database” and to the “Noninvasive Fetal Electrocardiography Database” of Physionet. R-peak detection accuracy was quantified by computation of positive-predictive value, sensitivity and F1 score. Results:When applied to “Abdominal and Direct Fetal Electrocardiogram Database”, the accuracy of the improved fetal Pan-Tompkins’ algorithm was significantly higher than the standard (positive-predictive value: 0.94 vs. 0.79; sensitivity: 0.95 vs. 0.80; F1 score: 0.94 vs. 0.79; P<0.05 in all cases) on indirect fetal electrocardiograms, whereas both methods performed similarly on direct fetal electrocardiograms (positive-predictive value, sensitivity and F1 score all close to 1). Improved fetal Pan-Tompkins’ algorithm was found to be superior to the standard also when applied to “Noninvasive Fetal Electrocardiography Database” (positive-predictive value: 0.68 vs. 0.55, P<0.05; sensitivity: 0.56 vs. 0.46, P=0.23; F1 score: 0.60 vs. 0.47, P=0.11).Conclusion:In indirect fetal electrocardiographic applications, improved fetal Pan-Tompkins’ algorithm is to be preferred over the standard, since it provides higher R-peak detection accuracy for heart-rate evaluations and subsequent processing.

Determination of fetal heart rate from abdominal signals: evaluation of beat-to-beat accuracy in relation to the direct fetal electrocardiogram.

The main aim of our work was to assess the reliability of indirect abdominal electrocardiography as an alternative to the commonly used Doppler ultrasound monitoring technique. As a reference method, we used direct fetal electrocardiography. Direct and abdominal signals were acquired simultaneously, using dedicated instrumentation. The developed method of maternal signal suppression as well as fetal QRS complexes detection was presented. Recordings were collected during established labors, each consisted of four signals from the maternal abdomen and the reference signal acquired directly from the fetal head. After assessing the performance of the QRS detector, the accuracy of fetal heart rate measurement was evaluated. Additionally, to reduce the influence of inaccurately detected R-waves, some validation rules were proposed. The obtained results revealed that the indirect method is able to provide an accuracy sufficient for a reliable assessment of fetal heart rate variability. However, the method is very sensitive to recording conditions, influencing the quality of signals. Our investigations confirmed that abdominal electrocardiography, even in its current stage of development, offers an accuracy equal to or higher than an ultrasound method, at the same time providing some additional features.

A novel technique for fetal heart rate estimation from Doppler ultrasound signal

BackgroundThe currently used fetal monitoring instrumentation that is based on Doppler ultrasound technique provides the fetal heart rate (FHR) signal with limited accuracy. It is particularly noticeable as significant decrease of clinically important feature - the variability of FHR signal. The aim of our work was to develop a novel efficient technique for processing of the ultrasound signal, which could estimate the cardiac cycle duration with accuracy comparable to a direct electrocardiography.MethodsWe have proposed a new technique which provides the true beat-to-beat values of the FHR signal through multiple measurement of a given cardiac cycle in the ultrasound signal. The method consists in three steps: the dynamic adjustment of autocorrelation window, the adaptive autocorrelation peak detection and determination of beat-to-beat intervals. The estimated fetal heart rate values and calculated indices describing variability of FHR, were compared to the reference data obtained from the direct fetal electrocardiogram, as well as to another method for FHR estimation.ResultsThe results revealed that our method increases the accuracy in comparison to currently used fetal monitoring instrumentation, and thus enables to calculate reliable parameters describing the variability of FHR. Relating these results to the other method for FHR estimation we showed that in our approach a much lower number of measured cardiac cycles was rejected as being invalid.ConclusionsThe proposed method for fetal heart rate determination on a beat-to-beat basis offers a high accuracy of the heart interval measurement enabling reliable quantitative assessment of the FHR variability, at the same time reducing the number of invalid cardiac cycle measurements.

Fetal autonomic response to severe acidaemia during labour

Spectral analysis of heart-rate variability is used to monitor autonomic nervous system fluctuations. The low-frequency component is associated with sympathetic and parasympathetic modulation and the high-frequency component is associated with parasympathetic modulation. The objective was to study whether changes in low-frequency or high-frequency power of heart-rate variability occur in case of fetal distress. Case-control study. Obstetric unit of a tertiary-care teaching hospital. Twenty healthy human fetuses during labour at term of which ten had an umbilical artery pH < 7.05 (cases), and ten had an arterial pH > 7.20 (controls) after birth. Spectral information about fetal beat-to-beat heart rate, calculated from direct fetal electrocardiogram registrations, was obtained by using a short-time Fourier transform. Absolute power and normalised power in the low-frequency and high-frequency bands. No differences were found between fetuses with and without acidaemia in absolute low or high frequency power (P = 0.2 and P = 0.3, respectively). During the last 30 minutes of labour, acidaemic fetuses had significantly increased normalised low-frequency power (P = 0.01) and decreased normalised high-frequency power (P = 0.03) compared with non-acidaemic fetuses. These differences were not observed from 3 to 2 hours before birth (P = 0.7 and P = 0.9, respectively). The autonomic nervous system of human fetuses at term responds adequately to severe stress during labour. Normalised low and high frequency power of heart-rate variability might be able to discriminate between normal and abnormal fetal condition.

Confirmation of the Distribution of Measured Values from an Ultrasound Fetal Heart Rate Monitor

To estimate the measurement error in an ultrasound fetal heart rate (FHR) monitor, we compared the differences in the distribution of the FHR measured with an ultrasound Doppler to the FHR measured with a direct fetal electrocardiogram. We confirm that (1) the distribution is very similar to Student's t distribution, and (2) the number of degrees of freedom in Student's t distribution has a significant impact on the evaluation of fit.

Needle modifications for invasive fetal procedures

To investigate the effect of needle size and siliconization on fetal blood sampling, transfusion, and electrocardiography. Standard needles were modified by increasing the internal (but not the external) diameter and either siliconization of the bore or external Teflon coating. The siliconized needles were subjected to a series of flow experiments with either blood or saline at various driving pressures, and assessed in clinical use during fetal transfusion and fetal blood sampling. The Teflon-coated needles were used for fetal transfusion to try and facilitate the fetal electrocardiogram (ECG). Under conditions simulating fetal transfusion, the siliconized needle allowed a 93% increase in flow rate compared to the standard needle (P < .05). Samples obtained after fetal transfusion with the siliconized needles were free of clots, whereas 50% of the post-transfusion samples with the standard needle had clots present. Similarly, samples taken for fetal platelet count were free of platelet clumping and clots with siliconized needles, but not with standard needles. Fetal ECG recordings were recorded successfully when Teflon-coated needles were used to access the fetal circulation via the intrahepatic vein. Modifications to standard needles improved blood flow and reduced the activation of coagulation during both fetal intravascular transfusion and platelet count measurement. Direct fetal ECG recording was facilitated by Teflon coating the external surface of the needle, insulating the fetal signal from maternal electrical signals.

A technique for intrapartum monitoring of fetuses with congenital bradycardias.

Our objective was to construct from readily available components a system that would allow determination of P-wave to P-wave intervals in fetuses with congenital heart block. Using a fetal monitor, bedside patient monitor, spiral electrode, and a special cable described herein, we obtained direct fetal electrocardiograms from two fetuses with autoimmune heart block. Measurement of the atrial rate was made by determining the P-wave to P-wave interval. These determinations were compared to atrial rates measured by M-mode echocardiography in utero and neonatal electrocardiograms. Atrial rates determined by direct fetal electrocardiogram were identical to rates obtained by M-mode echocardiography and within 10 beats/min of rates calculated from neonatal electrocardiograms. Premature ventricular contractions in one fetus were also detected. It is possible to perform continuous and accurate assessments of sinoatrial node activity in fetuses with congenital heart block using components readily available to most obstetricians.

QRS changes in direct fetal electrocardiogram during uterine overstimulation; report of four cases

Four cases are presented in which increased QRS complex voltages or deviation of the mean electrical axis were observed in the fetus by direct fetal electrocardiogram (ECG) during delivery under anaesthesia. There was transformation of the initial QRS aspect before delivery. These changes were only observed when large doses of oxytocin (20 IU in 500 ml) were used after Pentothal administration in deliveries in which other fetal ECG alterations (bradycardia, ST changes, T inversion) and/or low pH values had been observed. In case 1 there were ST level changes, inversion of the T wave and transformation of the QRS complex from RS to Rs. Case 2 showed a change from RS to QR type complex associated with repolarization defects. In cases 3 and 4, ST level changes, inversion and increased QRS complex voltages were observed. We checked that the modifications observed were not due to changes in position of the fetus during recording. It is thought that the acute redistribution of the fetal blood volume due to oxytocin overstimulation in fetal hearts with hypoxic signs may lead to compensatory mechanisms such as tachycardia, increased contractile activity (higher QRS) and functional predominance of one side of the fetal heart (deviation of the electrical axis) subjected to sudden load.