Maternal Abdominal Electrocardiogram Research Articles

Generalized recursive algorithm for fetal electrocardiogram isolation from non-invasive maternal electrocardiogram

Non-invasive maternal electrocardiogram recording is the least unpleasant method to record a weak fetal electrocardiogram signal. The importance of this recording lies in the fact that it reveals crucial information about the fetal health state, especially during the last four weeks of pregnancy. This paper will be concerned with a new adaptive algorithm, namely the generalized recursive algorithm, to isolate and get the fetal electrocardiogram from the abdominal maternal electrocardiogram. This is achieved using a non-invasive method for bi-channel maternal electrocardiogram recordings i.e., with the thoracic maternal electrocardiogram as a reference signal, and the abdominal maternal electrocardiogram as a primary signal. Prior to this procedure, the discrete wavelet transform (DWT) method is applied to the abdominal electrocardiogram signal to clean it from any additive noise and the baseline wandering that is generally present on the raw recordings. The proposed new adaptive filter is shown to deliver improved characteristics through simulations. These simulations were performed on both synthetic and actual signals. This work was compared with the normalized least mean square algorithm.

Frequency-Based Maternal Electrocardiogram Attenuation for Fetal Electrocardiogram Analysis

Fetal electrocardiogram (ECG) waveform analysis along with cardiac time intervals (CTIs) measurements are critical for the management of high-risk pregnancies. Currently, there is no system that can consistently and accurately measure fetal ECG. In this work, we present a new automatic approach to attenuate the maternal ECG in the frequency domain and enhance it with measurable CTIs. First, the coherent components between the maternal ECG and abdominal ECG were identified and subtracted from the latter in the frequency domain. The residual was then converted into the time domain using the inverse Fourier transform to yield the fetal ECG. This process was improved by averaging multiple beats. Two fetal cardiologists, blinded to the method, assessed the quality of fetal ECG based on a grading system and measured the CTIs. We evaluated the fetal ECG quality of our method and time-based methods using one synthetic dataset, one human dataset available in the public domain, and 37 clinical datasets. Among the 37 datasets analyzed, the mean average (± standard deviation) grade was 3.49 ± 1.22 for our method vs. 2.64 ± 1.26 for adaptive interference cancellation (p-value < 0.001), thus showing the frequency-based fetal ECG extraction was the superior method, as assessed from our clinicians’ perspectives. This method has the potential for use in clinical settings.

A Fetal ECG Monitoring System Based on the Android Smartphone.

In this paper, a fetal electrocardiogram (ECG) monitoring system based on the Android smartphone was proposed. We designed a portable low-power fetal ECG collector, which collected maternal abdominal ECG signals in real time. The ECG data were sent to a smartphone client via Bluetooth. Smartphone app software was developed based on the Android system. The app integrated the fast fixed-point algorithm for independent component analysis (FastICA) and the sample entropy algorithm, for the sake of real-time extraction of fetal ECG signals from the maternal abdominal ECG signals. The fetal heart rate was computed using the extracted fetal ECG signals. Experimental results showed that the FastICA algorithm can extract a clear fetal ECG, and the sample entropy can correctly determine the channel where the fetal ECG is located. The proposed fetal ECG monitoring system may be feasible for non-invasive, real-time monitoring of fetal ECGs.

Extraction of the Fetal Electrocardiogram Using Dynamic Neural Networks

This article presents a nonlinear dynamics model for discriminating the sources of the maternal abdominal elec-trocardiogram (aECG). The coefficients of the separating matrix were determined by training a neural network. This method provides efficient extraction of the fetal electrocardiogram (fECG) independently of the choice of recording point, input signal duration, or number of independent leads.

A new method to derive fetal heart rate from maternal abdominal electrocardiogram: monitoring fetal heart rate during cesarean section.

BackgroundMonitoring of fetal heart rate (FHR) is important during labor since it is a sensitive marker to obtain significant information about fetal condition. To take immediate response during cesarean section (CS), we noninvasively derive FHR from maternal abdominal ECG.MethodsWe recruited 17 pregnant women delivered by elective cesarean section, with abdominal ECG obtained before and during the entire CS. First, a QRS-template is created by averaging all the maternal ECG heart beats. Then, Hilbert transform was applied to QRS-template to generate the other basis which is orthogonal to the QRS-template. Second, maternal QRS, P and T waves were adaptively subtracted from the composited ECG. Third, Gabor transformation was applied to obtain time-frequency spectrogram of FHR. Heart rate variability (HRV) parameters including standard deviation of normal-to-normal intervals (SDNN), 0V, 1V, 2V derived from symbolic dynamics of HRV and SD1, SD2 derived from Poincareé plot. Three emphasized stages includes: (1) before anesthesia, (2) 5 minutes after anesthesia and (3) 5 minutes before CS delivery.ResultsFHRs were successfully derived from all maternal abdominal ECGs. FHR increased 5 minutes after anesthesia and 5 minutes before delivery. As for HRV parameters, SDNN increased both 5 minutes after anesthesia and 5 minutes before delivery (21.30±9.05 vs. 13.01±6.89, P < 0.001 and 22.88±12.01 vs. 13.01±6.89, P < 0.05). SD1 did not change during anesthesia, while SD2 increased significantly 5 minutes after anesthesia (27.92±12.28 vs. 16.18±10.01, P < 0.001) and both SD2 and 0V percentage increased significantly 5 minutes before delivery (30.54±15.88 vs. 16.18±10.01, P < 0.05; 0.39±0.14 vs. 0.30±0.13, P < 0.05).ConclusionsWe developed a novel method to automatically derive FHR from maternal abdominal ECGs and proved that it is feasible during CS.

Ex utero neonatal heart rate detection via non-invasive maternal abdominal electrocardiogram monitoring

Objective: A non-invasive fetal electrocardiogram (ECG) monitor has been approved for clinical usage in labour and delivery. To determine the feasibility of neonatal ECG signal detection via maternal abdominal non-invasive ECG monitor during bonding period.

Adaptive filtering in phase space for foetal electrocardiogram estimation from an abdominal electrocardiogram signal and a thoracic electrocardiogram signal

In this study, an adaptive filtering in phase space for foetal electrocardiogram (ECG) extraction from a maternal abdominal ECG signal and a thoracic ECG signal is proposed. The phase space trajectory is reconstructed with one abdominal ECG signal and one thoracic ECG signal from a pregnant women. The non-linear and time-variant relationship between the thoracic ECG signal and maternal ECG component in abdominal signal is built by the adaptive local modelling in phase space, and the maternal ECG component in abdominal ECG signal can be estimated, which is then subtracted from the abdominal ECG signal to obtain a foetal ECG estimate. The local modelling process is carried on the spatial neighbouring points of each point in phase space, not on the temporal neighbouring points of each point in time sequence as usual. This can utilise the geometric information of the periodic ECG signal, and the simpler local relationship represented in phase space makes the estimation of the relationship easier and more accurate. Compared with the classical adaptive filter, the proposed method has shown the improved robustness and fidelity in restoration of the foetal ECG, testing with synthetic and real ECG signals.

A Robust Real-Time Algorithm for Enhancing a Noninvasive Fetal Electrocardiogram

Currently, nonexperimental fetal electrocardiogram (FECG) systems are limited to the invasive scalp electrode that is used to monitor the status of a fetus or possibly determine a cardiac arrhythmia by heart rate (HR) determination. The invasive procedure can lead to complications and has a requirement of rupturing the fetal membranes that limit the monitoring time to immediately before delivery. A noninvasive procedure would allow physicians to obtain heart rate and electrophysiological information throughout the pregnancy without rupturing the membranes. The FECG noninvasive technique can be used to determine fetal status and cardiac arrhythmia similarly as the invasive procedure along with possibly the activity of the autonomic nervous system by spectral HR analysis, other clinical conditions that are being correlated with HR variability, and electrophysiological information such as acidosis and premature ventricular contractions. Finally, the noninvasive method can possibly be used to monitor uterine contracts through analyzing the abdominal electromyographic (AEMG) activity. Previously reported noninvasive procedures have not been commonly used in clinical practice because several different artifacts interfere with the FECG obtained from the abdominal area. The two most prevalent signals include the abdominal maternal electrocardiogram (AMECG) and AEMG interference from the cardiac and abdominal skeletal muscles of the mother. This paper discusses a computationally nonintensive robust real-time fetal monitoring system. The system consistently suppresses the AMECG in the presence of interfering signals, without filtering and/or distorting the electrophysiological information of the FECG and AEMG, and with two electrocardiogram leads. Furthermore, AMECG suppression can be obtained without canceling the FECG when the AMECG and FECG occur simultaneously. After AMECG attenuation, the FECG signal-to-noise ratio is improved by averaging a relatively small number of FECG complexes to avoid distorting the electrophysiological information of the FECG. Clinical data from 13 patients were used to test the algorithm′s robustness. The results from these data sets will be presented.

Computerized detection of low-level fetal signals in the maternal abdominal electrocardiogram

This paper describes a method for detecting low-level fetal ECG signals in maternal abdominal ECG recordings. Detection is based on a systematic application of the principle that the fetal ECG contains proportionately greater high-frequency components than does the maternal ECG. Adaptive subtraction of the maternal high-frequency components is used to detect the fetal R-waves. The method is found to detect the fetal ECG even in many cases where the maternal and fetal R-waves coincide or occur in close proximity to each other. Recursive time-coherent averaging is then used to significantly improve the signal-to-noise ratio of the fetal ECG to the point where the fetal P and T waves may be observed.

The simulation of the abdominal MECG.

In order to obtain an insight into the surface potential distribution of the maternal electrocardiogram (MECG) on the abdomen during pregnancy, a simulation model is set up. As a function of the shape of the abdomen and the internal conduction difference between uterus and surroundings, the surface potentials are calculated on a ring at the umbilicus level for the x, y, and z components of the maternal heart vector.