A Novel Technique for Fetal ECG Extraction Using Single-Channel Abdominal Recording

Abstract

Non-invasive fetal electrocardiograms (FECGs) are an alternative method to standard means of fetal monitoring which permit long-term continual monitoring. However, in abdominal recording, the FECG amplitude is weak in the temporal domain and overlaps with the maternal electrocardiogram (MECG) in the spectral domain. Research in the area of non-invasive separations of FECG from abdominal electrocardiograms (AECGs) is in its infancy and several studies are currently focusing on this area. An adaptive noise canceller (ANC) is commonly used for cancelling interference in cases where the reference signal only correlates with an interference signal, and not with a signal of interest. However, results from some existing studies suggest that propagation of electrocardiogram (ECG) signals from the maternal heart to the abdomen is nonlinear, hence the adaptive filter approach may fail if the thoracic and abdominal MECG lack strict waveform similarity. In this study, singular value decomposition (SVD) and smooth window (SW) techniques are combined to build a reference signal in an ANC. This is to avoid the limitation that thoracic MECGs recorded separately must be similar to abdominal MECGs in waveform. Validation of the proposed method with r01 and r07 signals from a public dataset, and a self-recorded private dataset showed that the proposed method achieved F1 scores of 99.61%, 99.28% and 98.58%, respectively for the detection of fetal QRS. Compared with four other single-channel methods, the proposed method also achieved higher accuracy values of 99.22%, 98.57% and 97.21%, respectively. The findings from this study suggest that the proposed method could potentially aid accurate extraction of FECG from MECG recordings in both clinical and commercial applications.

Comparative Effectiveness of ICA and PCA in Extraction of Fetal ECG From Abdominal Signals: Toward Non-invasive Fetal Monitoring

“…Tables 1 , 2 show the calculated values of these parameters for the analyzed records. For the detection of the fQRS complexes, we used an extended version of the Pan and Tompkins algorithm (Pan and Tompkins, 1985 ); and the accuracy of the fECG estimation was evaluated by a beat-to-beat comparison of the extracted fQRS complexes by means of the ICA or PCA methods and the reference fQRS complexes detected in the reference fECG signal acquired by the FSE (Zhang et al, 2017 ). …”

“…Techniques utilizing a multi-channel signal source include multiple and single-source methods. Single-channel signal source methods are based on for example Wavelet Transform (WT), Karvounis et al ( 2004 ), Datian and Xuemei ( 1996 ), Hassanpour and Parsaei ( 2007 ), Bsoul ( 2015 ), Ivanushkina et al ( 2014 ), Abburi and Chandrasekhara Sastry ( 2012 ), Bensafia et al ( 2017 ), Castillo et al ( 2013 ), Correlation Techniques De Araujo et al ( 2005 ), Averaging Techniques (AT) Hon and Lee ( 1963 ), Hon and Lee ( 1964 ), Template Subtraction Tsui et al ( 2017 ), Singular Value Decomposition (SVD) Kanjilal et al ( 1997 ), Adaptive Noise Canceler (ANC) Zhang et al ( 2017 ), and so on.…”

A Novel Antibacterial Membrane Electrode Based on Bacterial Cellulose/Polyaniline/AgNO3 Composite for Bio-Potential Signal Monitoring

“…Similarly, the second pair of the traditional Ag/AgCl gel electrodes (described in Section III , Part C) was used to quantify the amplitude reduction of the ECG signals alongside the co-located proposed electrodes. The R-wave peak in each cardiac cycle was detected according to the method in described [42] , [43] .…”

An Improved FastICA Method for Fetal ECG Extraction

“…At present, fetal ECG extraction algorithms mainly include adaptive filtering [ 4 , 5 ], wavelet analysis [ 6 ], matched filtering [ 7 ], blind source separation [ 8 ], independent component analysis (ICA) [ 9 ], neural network [ 10 , 11 ], and singular value decomposition (SVD) [ 12 ]. Among these methods, ICA can separate the source signals from the mixed signals under the assumption that the source signals are statistically independent of each other, without needing any information regarding the source signals or the mixed matrix.…”