Extraction of Fetal Heart Rate and Fetal Heart Rate Variability from Mother's ECG Signal (original) (raw)
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Methodological Survey on Fetal ECG Extraction
Abstract: Fetal Electrocardiogram (FECG) signal, non-invasively taken from the Abdominal Electrocardiogram (AECG) of a pregnant woman is a efficient diagnostic tool for evaluating the health status of fetus. Clinically significant information in the Fetal Electrocardiogram signal is often masked by Maternal Electrocardiogram (MECG) considered as the most predominant interference, power line interference, and maternal Electromyogram (EMG), baseline wander etc. Fetal Electrocardiogram signal features may not be readily comprehensible by the visual or auditory systems of a human. Therefore Fetal Electrocardiogram should be extracted from composite Abdominal Electrocardiogram for clinical diagnosis. There are many powerful and well advanced methods for this purpose. A methodological study has been carried out to show the effectiveness of various methods which helps in understanding of Fetal ECG signal and its analysis procedures by providing valuable information. Keywords: AbdominalECG, MaternalECG, ElectroMyoGram
De-noising of Fetal ECG for Fetal Heart Rate Calculation and Variability Analysis
Fetal monitoring is the way of checking the condition of unborn baby during labor and delivery by continuously monitoring his or her heart rate. A normal fetal heart rate (FHR) can reassure safe birth of the baby. Fetal monitoring techniques are broadly classified into invasive and non-invasive techniques. Non-invasive techniques are involves monitoring the fetus through mother's abdominal region. This can be done in all gestation weeks and during the delivery also. Abdominal ECG (AECG) is a composite ECG signal containing both mother's as well as fetal ECG. This paper presents an efficient technique to extract FECG from abdominal ECG. A modified Pan Tompkin's method is employed for the QRS detection. It involves series of filters and methods like band pass filter, derivative filter, squaring, integration and adaptive thresholding. Further heart rate of fetus and mother is calculated and heart rate variability analysis is done using detected R-peaks. The algorithm is tested on 5 different non-invasively recorded abdominal and direct FECG signals taken from MIT PhysioNet database and the results are obtained using MATLAB software. The performance of the QRS detector is evaluated using parameters like Sensitivity and Positive Prediction.
An Automated Methodology for Fetal Heart Rate Extraction From the Abdominal Electrocardiogram
IEEE Transactions on Information Technology in Biomedicine, 2000
This paper introduces an automated methodology for the extraction of fetal heart rate from cutaneous potential abdominal ECG recordings. A three-stage methodology is proposed. Having the initial recording, which consists of a small number of abdominal ECG leads, in the first stage the maternal R-peaks and fiducial points (QRS onset and offset) are detected, using time-frequency analysis and medical knowledge. Then, the maternal QRS complexes are eliminated. In the second stage the positions of the candidate fetal R-peaks are located using complex wavelets and matching theory techniques. In the third stage, the fetal R-peaks which overlap with the maternal QRS complexes (eliminated in the first stage) are found using two approaches: a heuristic algorithm and a histogram-based technique. The fetal Rpeaks detected, are used to calculate the fetal heart rate. The methodology is validated using a dataset of 8 short and 10 long duration recordings, obtained between the 20th and the 41st week of gestation and the obtained accuracy is 97.47%. The proposed methodology is advantageous since it is based on the analysis of few abdominal leads, in contrast to other proposed methods which need a large number of leads.
Proceedings
Here, we propose a signal processing based approach for the extraction of the fetal heart rate (FHR) from Maternal Abdominal ECG (MAECG) in a non-invasive way. Datasets from a Physionet database has been used in this study for evaluating the performance of the proposed model that performs three major tasks; preprocessing of the MAECG signal, separation of Fetal QRS complexes from that of maternal and estimation of Fetal R peak positions. The MAECG signal is first preprocessed with improved multistep filtering techniques to detect the Maternal QRS (MQRS) complexes, which are dominant in the MAECG. A reference template is then reconstructed based on MQRS locations and removed from the preprocessed signal resulting in the raw FECG. This extracted FECG is further corrected and enhanced before obtaining the Fetal R peaks. The detection of FQRS and calculation of FHR has been compared against the reference Fetal Scalp ECG. Results indicate that the approach achieved good accuracy.
Fetal heart rate variability extraction by frequency tracking
Proceedings of ICA, 2001
In this work, we propose an algorithm to extract the fetal heart rate variability from an ECG measured from the mother abdomen. The algorithm consists of two methods: a separation algorithm based on second-order statistics that extracts the desired signal in one shot through the data, and a heart instantaneous frequency (HIF) estimator. The HIF algorithm is used to extract the mother heart rate which serves as reference to extract the fetal heart rate. We carried out simulations where the signals overlap in frequency and time, and showed that it worked e ciently.
Comparison of Cardiotocography and Fetal Heart Rate Estimators Based on Non-Invasive Fetal ECG
2019 Computing in Cardiology Conference (CinC)
Non-invasive fetal ECG (NI-FECG) extraction algorithms enable long-term continuous beat-to-beat monitoring of the fetal heart rate (FHR), as opposed to the gold standard in FHR monitoring, cardiotocography (CTG). We investigate how NI-FECG extraction algorithms selected from the CinC 2013 Challenge (CinC13) perform on data with low quality signals and how performance can be evaluated using CTG, when FQRS annotation is not possible. Four-channel NI-FECG was recorded simultaneously with a CTG trace on 22 pregnant women, gestational age 29-41 weeks. Seven algorithms were tested: The winning CinC13 entry from Varanini et al. and six algorithms from the unofficial top-scoring CinC13 entry by Behar et al. Two accuracy measures were used: 1) The RMSE between the FECG-based FHR and CTG traces; 2) The Pearson correlation coefficient r between the FECG-based FHR and CTG trace and its average over all recordings,r. The algorithms with the lowest RMSE's are Behar's FUSE-SMOOTH, a constant FHR, and Varanini, while the Varanini algorithm delivers the best correlation with the CTG trace (r = 0.73) with 41% of the recordings having r > 0.8, whereas the other algorithms haver ≤ 0.59 and ≤ 29% of the recordings with r > 0.8. FHR was estimated accurately in some recordings and poorly in others, believed to be due to large differences in signal quality.
Extracting the fetal heart rate variability using a frequency tracking algorithm
Neurocomputing, 2002
In this work, we propose an algorithm to extract the fetal heart rate variability from an ECG measured from the mother abdomen. The algorithm consists of two methods: a separation algorithm based on second-order statistics that extracts the desired signal in one shot through the data, and a heart instantaneous frequency (HIF) estimator. The HIF algorithm is used to extract the mother heart rate which serves as reference to extract the fetal heart rate. We carried out simulations where the signals overlap in frequency and time, and showed that it worked e ciently.
An Algorithm for Fetal ECG Extraction from the Composite Abdominal Signal
2016
The electrical activity of the fetus heart is basically the fetal electrocardiogram.FECG is a weak signal which is measured indirectly by placing the electrode on the surface abdomen of the mother. The Fetal signals contains many other interfering signal. Extraction of the fetal ECG parameters from the abdominal signal has an important value in clinical application and also enables continuous monitoring of the fetus status by means of analyzing its cardiac activity. This paper proposes a non-invasive method for the FECG extraction by using a template for the cancellation of maternal QRS complex. The final results specify that the fetal R peaks can be easily detected under various circumstances without using the reference maternal thoracic signal. IndexTerms—AECG(AbdominalElectrocardiogram), FECG(Fetal Electrocardiogram), FHR(Fetal Heart Rate), MECG (Mother’s Electrocardiogram).
Detection of fetal arrhythmia by adaptive single channel electrocardiogram extraction
Physical and Engineering Sciences in Medicine, 2021
Fetal arrhythmia, the abnormal heartbeat of a fetus is broadly classified as tachy arrhythmia (too fast > 160 beats/min) and brady arrhythmia (too slow < 120 beats/min). Detection of this irregular heart beat rhythm of the fetus during pregnancy is still a challenging task for the clinicians. Heart rate detection through electrocardiography has always been accurate for identifying cardiac defect in humans. Adult ECG has achieved several developments in the modern medicine whereas noninvasive fetal ECG (FECG) continues to be a big challenge. Automatic detection of fetal heart rate is vital for monitoring the unborn infant during pregnancy. The non-invasive placement of electrodes over the abdomen region of pregnant women records the ECG signal of both mother and fetus. The arrhythmia affected FECG signals (n = 14) are processed from the physionet database. This raw ECG signal is preprocessed using a Savitzky-Golay filter and symlet wavelet transform to remove the basic noises. Adaptive recursive least square filter is preferably chosen for extracting the FECG, using mother's thorax ECG as a reference. An accurate PQRST wave-shape of the FECG is required for the proper diagnosis of fetal cardiac defects. Using a single channel abdominal ECG signal, the proposed work generates extracted fetal ECG and an automated visual display of fetal heart rate. The presence of arrhythmia and fetal distress can be analyzed through fetal heart rate display and abnormal conductivity of PQRST wave respectively. We have analyzed fetal arrhythmias through ECG extraction and the same was compared with the echocardiograph results given by pediatric cardiologist. This study helps to identify the fetal distress at early gestational age that helps the obstetricians to make quick decisions before or immediately after delivery.
A New Approach for Extracting and Characterizing Fetal Electrocardiogram
Traitement du Signal
This paper presents a new approach for extracting and characterizing the fetal electrocardiogram from a mixture of maternal and fetal electrocardiograms, which is of very low amplitude and therefore its medical characterization would be very difficult and unreliable. This method is based on timescale analysis by using Continuous Wavelet Transform and the Scalogram. Previous work in this field has only investigated on time and time-frequency methods using the Short Fourier Transform, which does not give convincing and accurate results for biomedical signals that require high precision because any part of the extracted signal may indicate a dangerous pathology. The effectiveness of this approach lies in the fact that the timescale analysis or scalogram of fetal-maternal electrocardiogram mixture has several energetic zones corresponding either to the electrical activity of the heart of the fetus or of her mother, which it facilitates considerably the use of these diagrams in order to separate maternal and fetal electrocardiograms. Compared to other more recent, the results found by simulations are very interesting and the extracted signal corresponds approximately to the source. As a consequence, we can characterize and extract all useful medical parameters. More importantly, our approach can be implemented on real time life by using embedded system such as Raspberry and Digital Signal Processor.