Automatic identifying of maternal ECG source when applying ICA in fetal ECG extraction

• Autorzy: Yu Q. , Yan H. , Song L. , Guo W. , Liu H. , Si J. , Zhao Y.

Identyfikatory

DOI

10.1016/j.bbe.2018.03.003

• Języki publikacji: EN

Abstrakty

EN

Independent component analysis (ICA) is usually used as a preliminary step for maternal electrocardiogram (ECG) QRS detection in fetal ECG extraction. When applying ICA to do this, a troublesome problem arises from how to automatically identify the separated maternal ECG component. In this paper we proposed a method called PRCH (short for Peak to peak entropy, R-R interval entropy, Correlation coefficient and Heart rate) for the automatic identifying. In the method, we defined four kinds of features, including amplitude, instantaneous heart rate, morphology and average heart rate, to characterize a signal, and determined some decision parameters through machine learning. Experiments and comparison with other three existed methods were given. Through taking metric F1 for evaluation, it showed that the proposed PRCH method has the highest identifying accuracy and generalization capability.

Słowa kluczowe

EN

fetal ECG extraction; independent component analysis; automatic identification; ECG features

PL

EKG płodu; analiza składowych niezależnych; identyfikacja automatyczna

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2018
• Tom: Vol. 38, no. 3
• Strony: 448--455
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wykr.

Twórcy

autor

Yu Q.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Yan H.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Song L.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Guo W.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Liu H.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Si J.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

autor

Zhao Y.

• School of Electronic Science and Engineering, Nanjing University, Xianlin Campus, Nanjing 210023, China

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).