4.7 Article Data Paper

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

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SCIENTIFIC DATA
卷 8, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41597-021-00811-3

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资金

  1. Sardinia Regional Government
  2. Italian Government Progetti di Interesse Nazionale (PRIN) [2017RR5EW3]
  3. European Research Council [320684]
  4. European Research Council (ERC) [320684] Funding Source: European Research Council (ERC)

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The NInFEA dataset is the first multimodal early-pregnancy dataset designed for research on antenatal cardiology, providing simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler. It includes 60 entries from 39 pregnant women between the 21st and 27th week of gestation, with MATLAB snippets for data processing provided.
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 21(st) and 27(th) 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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