Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Matonia, A.; Jeżewski, Janusz; Kupka, T.; Jeżewski, Michał; Horoba, K.; Wróbel, Janusz; Czabański, Robert; Kahankowa, Radana

doi:10.1038/s41597-020-0538-z

Cited by 58 publications

(43 citation statements)

References 66 publications

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“…The advantage of this dataset is the presence of a direct (invasive) reference fECG, which can be used as a gold standard, along with the length of the traces, which are five minutes long. The most recent dataset made publicly available was proposed by Matonia et al 23 , which shares signals with ADFECGDB. This dataset was acquired with the Komporel system, partly in late pregnancy (32nd to 42nd weeks) and partly during labour (between the 38th and 42nd weeks).…”

Section: Background and Summarymentioning

confidence: 99%

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

et al. 2021

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Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided.

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Section: Background and Summarymentioning

confidence: 99%

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

et al. 2021

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“…In this study, two databases were used to test the performance of the ICA-RLS-EEMD extraction method. The first one is called the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations (FECGDARHA) and is available in the figshare repository [82]. It contains 12 real recordings acquired from 12 different women, in 38-42 week of pregnancy.…”

Section: Datasetmentioning

confidence: 99%

A novel algorithm based on ensemble empirical mode decomposition for non-invasive fetal ECG extraction

et al. 2021

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Non-invasive fetal electrocardiography appears to be one of the most promising fetal monitoring techniques during pregnancy and delivery nowadays. This method is based on recording electrical potentials produced by the fetal heart from the surface of the maternal abdomen. Unfortunately, in addition to the useful fetal electrocardiographic signal, there are other interference signals in the abdominal recording that need to be filtered. The biggest challenge in designing filtration methods is the suppression of the maternal electrocardiographic signal. This study focuses on the extraction of fetal electrocardiographic signal from abdominal recordings using a combination of independent component analysis, recursive least squares, and ensemble empirical mode decomposition. The method was tested on two databases, the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations and the PhysioNet Challenge 2013 database. The evaluation was performed by the assessment of the accuracy of fetal QRS complexes detection and the quality of fetal heart rate determination. The effectiveness of the method was measured by means of the statistical parameters as accuracy, sensitivity, positive predictive value, and F1-score. Using the proposed method, when testing on the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database, accuracy higher than 80% was achieved for 11 out of 12 recordings with an average value of accuracy 92.75% [95% confidence interval: 91.19–93.88%], sensitivity 95.09% [95% confidence interval: 93.68–96.03%], positive predictive value 96.36% [95% confidence interval: 95.05–97.17%] and F1-score 95.69% [95% confidence interval: 94.83–96.35%]. When testing on the Physionet Challenge 2013 database, accuracy higher than 80% was achieved for 17 out of 25 recordings with an average value of accuracy 78.24% [95% confidence interval: 73.44–81.85%], sensitivity 81.79% [95% confidence interval: 76.59–85.43%], positive predictive value 87.16% [95% confidence interval: 81.95–90.35%] and F1-score 84.08% [95% confidence interval: 80.75–86.64%]. Moreover, the non-invasive ST segment analysis was carried out on the records from the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database and achieved high accuracy in 7 from in total of 12 records (mean values μ < 0.1 and values of ±1.96σ < 0.1).

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“…database that includes a continuous reference scalp recordings in addition to abdominal ones so that the accuracy of the NI-fECG can be evaluated. Only one publicly available database (ADFECGDB) meets these criteria, thus we used it in our experiments [23], [39], [103]. These recordings were obtained from 12 subjects between the 38 th and 41 st week of pregnancy.…”

Section: A Datasetmentioning

confidence: 99%

“…Each includes four abdominal and one direct signal along with the annotations indicating the location of the fetal R peaks. These annotations were created by online analysis in the KOMPOREL system and verified by a group of cardiologists [39], [103]. The sampling frequency was 1000 Hz (for five recordings) and 500 Hz (for seven recordings), the signal resolution was 16 bits.…”

Section: A Datasetmentioning

confidence: 99%

“…The abdominal signals were recorded using the Ag-AgCl electrodes, while the direct signals were recorded by means of spiral fetal scalp electrode. The configuration of the abdominal electrodes comprised four electrodes placed on the abdomen, an abdominal reference electrode placed above the pubic symphysis and a common mode reference electrode (with active-ground signal) placed on the left leg [39], [103].…”

Section: A Datasetmentioning

confidence: 99%

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

et al. 2021

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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 traditionalgold 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. INDEX TERMS Non-invasive fetal electrocardiography (NI-fECG), fetal heart rate (fHR), ST segment analysis (ST-analysis), hybrid method (HM), independent component analysis and recursive least squares (ICA-RLS), electronic fetal monitoring (EFM), fetal distress (FD), fetal scalp electrode (FSE).

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Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Cited by 58 publications

References 66 publications

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

A novel algorithm based on ensemble empirical mode decomposition for non-invasive fetal ECG extraction

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

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