Physiological Measurement · 2014 · 208 citations · 37 references
EngineeringBioengineeringCardiologyBioinstrumentationBiomedical Signal ProcessingClinical CardiologyCardiac Signal ProcessingElectrocardiogram AnalysisElectrocardiographyFetal CardiologyFetal Signal ProcessingPhysiological Signal AcquisitionEcg Feature ExtractionElectrocardiogram Feature ExtractionFetal Electrocardiogram AnalysisFetal ElectrocardiographyPhysiological MeasurementQrs Complex DetectionQt Interval AnalysisQt Interval Assessment
NI‑FECG analysis remains challenging because no gold‑standard database exists and prior studies rely on limited proprietary data, prompting the 2013 PhysioNet/Computing in Cardiology Challenge to provide public data for algorithm evaluation. The Challenge aimed to foster accurate algorithms for locating QRS complexes and estimating QT intervals in NI‑FECG signals. The Challenge used carefully reviewed reference QRS and QT annotations, sometimes from simultaneous direct FECG, to objectively measure and compare participants’ algorithm performance across events testing FHR, RR, and QT interval estimation. The editorial highlights key achievements and follow‑up research stemming from the Challenge, as published in a special issue of Physiological Measurement.
Despite the important advances achieved in the field of adult electrocardiography signal processing, the analysis of the non-invasive fetal electrocardiogram (NI-FECG) remains a challenge. Currently no gold standard database exists which provides labelled FECG QRS complexes (and other morphological parameters), and publications rely either on proprietary databases or a very limited set of data recorded from few (or more often, just one) individuals.The PhysioNet/Computing in Cardiology Challenge 2013 enables to tackle some of these limitations by releasing a set of NI-FECG data publicly to the scientific community in order to evaluate signal processing techniques for NI-FECG extraction. The Challenge aim was to encourage development of accurate algorithms for locating QRS complexes and estimating the QT interval in non-invasive FECG signals. Using carefully reviewed reference QRS annotations and QT intervals as a gold standard, based on simultaneous direct FECG when possible, the Challenge was designed to measure and compare the performance of participants' algorithms objectively. Multiple challenge events were designed to test basic FHR estimation accuracy, as well as accuracy in measurement of inter-beat (RR) and QT intervals needed as a basis for derivation of other FECG features.This editorial reviews the background issues, the design of the Challenge, the key achievements, and the follow-up research generated as a result of the Challenge, published in the concurrent special issue of Physiological Measurement.
37
PhysioBank, PhysioToolkit, and PhysioNet
Ary L. Goldberger, Luı́s A. Nunes Amaral, Leon Glass et al. · Circulation · 2000 · 14.5K citations · Full text
A Real-Time QRS Detection Algorithm
Jiapu Pan, W.J. Tompkins · IEEE Transactions on Biomedical Engineering · 1985 · 7.7K citations
A robust fetal ECG detection method for abdominal recordings
Suzanna Martens, Chiara Rabotti, Massimo Mischi et al. · Physiological Measurement · 2007 · 191 citations