A simple noninvasive approach for fetal electrocardiogram extraction based on wavelet transform

Bsoul, Abed Al Raoof

doi:10.1109/icabme.2015.7323260

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Indirect measurement involves non-invasive FECG recordings that are obtained by placing a skin electrode on the mother’s abdomen. Fetal monitoring is based entirely on the FHR because there is no available technology to reliably measure FECG (Chandraharan, 2010 ; Anisha et al, 2014 ; Bsoul, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

Alnuaimi

Jimaa

Khandoker

2017

Front. Bioeng. Biotechnol.

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The fetal Doppler Ultrasound (DUS) is commonly used for monitoring fetal heart rate and can also be used for identifying the event timings of fetal cardiac valve motions. In early-stage fetuses, the detected Doppler signal suffers from noise and signal loss due to the fetal movements and changing fetal location during the measurement procedure. The fetal cardiac intervals, which can be estimated by measuring the fetal cardiac event timings, are the most important markers of fetal development and well-being. To advance DUS-based fetal monitoring methods, several powerful and well-advanced signal processing and machine learning methods have recently been developed. This review provides an overview of the existing techniques used in fetal cardiac activity monitoring and a comprehensive survey on fetal cardiac Doppler signal processing frameworks. The review is structured with a focus on their shortcomings and advantages, which helps in understanding fetal Doppler cardiogram signal processing methods and the related Doppler signal analysis procedures by providing valuable clinical information. Finally, a set of recommendations are suggested for future research directions and the use of fetal cardiac Doppler signal analysis, processing, and modeling to address the underlying challenges.

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Section: Introductionmentioning

confidence: 99%

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

Alnuaimi

Jimaa

Khandoker

2017

Front. Bioeng. Biotechnol.

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“…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.…”

Section: State Of the Artmentioning

confidence: 99%

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

et al. 2018

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Non-adaptive signal processing methods have been successfully applied to extract fetal electrocardiograms (fECGs) from maternal abdominal electrocardiograms (aECGs); and initial tests to evaluate the efficacy of these methods have been carried out by using synthetic data. Nevertheless, performance evaluation of such methods using real data is a much more challenging task and has neither been fully undertaken nor reported in the literature. Therefore, in this investigation, we aimed to compare the effectiveness of two popular non-adaptive methods (the ICA and PCA) to explore the non-invasive (NI) extraction (separation) of fECGs, also known as NI-fECGs from aECGs. The performance of these well-known methods was enhanced by an adaptive algorithm, compensating amplitude difference and time shift between the estimated components. We used real signals compiled in 12 recordings (real01–real12). Five of the recordings were from the publicly available database (PhysioNet-Abdominal and Direct Fetal Electrocardiogram Database), which included data recorded by multiple abdominal electrodes. Seven more recordings were acquired by measurements performed at the Institute of Medical Technology and Equipment, Zabrze, Poland. Therefore, in total we used 60 min of data (i.e., around 88,000 R waves) for our experiments. This dataset covers different gestational ages, fetal positions, fetal positions, maternal body mass indices (BMI), etc. Such a unique heterogeneous dataset of sufficient length combining continuous Fetal Scalp Electrode (FSE) acquired and abdominal ECG recordings allows for robust testing of the applied ICA and PCA methods. The performance of these signal separation methods was then comprehensively evaluated by comparing the fetal Heart Rate (fHR) values determined from the extracted fECGs with those calculated from the fECG signals recorded directly by means of a reference FSE. Additionally, we tested the possibility of non-invasive ST analysis (NI-STAN) by determining the T/QRS ratio. Our results demonstrated that even though these advanced signal processing methods are suitable for the non-invasive estimation and monitoring of the fHR information from maternal aECG signals, their utility for further morphological analysis of the extracted fECG signals remains questionable and warrants further work.

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A simple noninvasive approach for fetal electrocardiogram extraction based on wavelet transform

Cited by 2 publications

References 13 publications

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

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

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