Physiological Measurement · 2019 · 20 citations · 60 references
EngineeringBiomedical EngineeringCardiologyBioinstrumentationBiomedical Signal ProcessingElectrophysiologyCardiac Signal ProcessingElectrocardiogram AnalysisElectrocardiographyFetal CardiologyFetal MonitoringFetal Signal ProcessingEcg Morphology AnalysisEcg Signal ReconstructionFeature Extraction From Fetal SignalsFetal Arrhythmia DetectionFetal Ecg Signal SeparationFetal Electrocardiogram AnalysisFetal R-peak DetectionR Peak Detection
OBJECTIVE: We propose a novel algorithm to recover fetal electrocardiogram (ECG) for both the fetal heart rate analysis and morphological analysis of its waveform from two or three trans-abdominal maternal ECG channels. APPROACH: We design an algorithm based on the optimal-shrinkage under the wave-shape manifold model. For the fetal heart rate analysis, the algorithm is evaluated on publicly available database, 2013 PhyioNet/Computing in Cardiology Challenge, set A (CinC2013). For the morphological analysis, we analyze CinC2013 and another publicly available database, non-invasive fetal ECG arrhythmia database (nifeadb), and propose to simulate semi-real databases by mixing the MIT-BIH normal sinus rhythm database and MITDB arrhythmia database. MAIN RESULTS: For the fetal R peak detection, the proposed algorithm outperforms all algorithms under comparison. For the morphological analysis, the algorithm provides an encouraging result in recovery of the fetal ECG waveform, including PR, QT and ST intervals, even when the fetus has arrhythmia, both in real and simulated databases. SIGNIFICANCE: To the best of our knowledge, this is the first work focusing on recovering the fetal ECG for morphological analysis from two or three channels with an algorithm potentially applicable for continuous fetal electrocardiographic monitoring, which creates the potential for long term monitoring purpose.
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