Non-Adaptive Methods of Fetal ECG Signal Processing

Kahánková, Radana; Jaroš, René; Martínek, Radek; Jeżewski, Janusz; Wen, He; Jeżewski, Michał; Kawala-Janik, Aleksandra

doi:10.15598/aeee.v15i3.2196

Cited by 23 publications

(22 citation statements)

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“…Non-adaptive methods have been applied to the fECG signal extraction problem (Kahankova et al, 2017b ), and initial investigations have been carried out by using synthetic data from a novel signal generator (Martinek et al, 2015b , 2016b ). Nevertheless, performance verification of the applied methods using real data is a more complex task than testing them with synthetic signals.…”

Section: Methodsmentioning

confidence: 99%

“…The multi-source methods are based on Subspace Denoising Fatemi and Sameni ( 2017 ) or Blind Source Separation (BSS), namely: Independent Component Analysis (ICA), Martín-Clemente et al ( 2011 ), Vrins et al ( 2004 ), Najafabadi et al ( 2006 ), Mochimaru et al ( 2004 ), Sameni et al ( 2007 ), De Lathauwer et al ( 2000 ), Marossero et al ( 2003 ), Gurve et al ( 2017 ), Billeci and Maurizio ( 2017 ); Principal Component Analysis (PCA), Gurve et al ( 2017 ), Kahankova et al ( 2017b ), and so on. BSS is a frequently used method for fECG signal filtering.…”

Section: State Of the Artmentioning

confidence: 99%

“…Consequently, to complement our previous work and compare the effectiveness of non-adaptive signal processing methods in suppressing the mECG signals, we carried out the current investigation focusing on the Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The results of our initial experiments applying the popular PCA and ICA methods to synthetic data are presented and reported elsewhere (Kahankova et al, 2017a ). The next logical step was to expand our previous work and perform our experiments using real data.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Methodsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

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“…There are many methods of the so-called time-frequency analysis, which allow to visualize the course of spectrum variability of signals over time. One of the basic ones is the so-called short time Fourier transform (STFT) [29][30][31]. It is founded upon the fact that the analysis window is shifted along the time axis, and after each shift the FFT signal inside the window is calculated.…”

Section: Characteristics Of the Test Circuit Signals (Stft Analysis)mentioning

confidence: 99%

Diagnostic approach in assessment of a ferroresonant circuit

Majka

Klimas

2019

Electr Eng

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This paper presents possibilities offered by a diagnostic system called FeD. The system is completely original; it has been developed by the authors on the basis of Arduino platform. The system has been designed to perform and record measurements and to carry out different numerical operations. The real-time function for several operations is incorporated in this system. The necessary input data for the system consist of the electrical voltage waveforms only. Rescaled voltage quantities can be displayed, measured, recorded or computed in any chosen way. The system has been developed particularly for measurements and computations in the ferroresonant circuits. The strongest part of the system is its versatility. It works with a standard PC and supports a universal connection (USB standard). This is undeniably a cost-wise solution. Driving and control of the system functions are carried out using the authors' original software implemented in SciLab environment. This is free software, similar to and compatible with other existing CAD programs such as Octave and MATLAB. The obtained data, scripts and results can be freely transferred between them. The program is equipped with a transparent GUI. The need of constructing a special system to diagnose the ferroresonant circuit has emerged during earlier ferroresonance analyses and computations. Every ferroresonant circuit requires specific kind of diagnostics to estimate and display its base features in order to determine the best scientific approach to the problem. The ferroresonance phenomenon belongs to the domain of nonlinear problems. Its analysis requires excellent skills in mathematics and physics as well as computer science. Moreover, this subject also requires specialized engineering knowledge, particularly in the field of power engineering and power system equipment. Modern mathematical models and analyses used in ferroresonant computations are quite accurate; however, in case of a common user, they are often difficult to understand or implement. This paper provides full description of construction, features and test results of the developed hardware/software system designed for diagnostics of ferroresonant circuits. The test circuit case study has been performed in the entire power supply range. Results of measurements and computations as well as screenshots captured from authors' original software are shown in different figures. The developed software and recorded data have been finally used in modeling and further simulations. During this, the application of the fractional derivative iron core coil model to ferroresonance analysis has been shown. The waveforms obtained from computer simulations have been compared with those obtained from measurements performed in the test circuit.

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“…Some issues, such as premature birth, hypoxia, or intrauterine retardation, are dangerous both for the fetus and for the mother. Fetal monitoring includes methods such as fetal electrocardiography (fECG) [ 1 , 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 ], fetal phonocardiography (fPCG) [ 4 , 5 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ], fetal echocardiography (fECHO) [ 22 , 23 , 24 , 25 ], fetal magnetocardiography (fMCG) [ 26 , 27 , 28 , 29 , 30 ], and cardiotocography (CTG) [ 9 , 31 , 32 , 33 ], which is based on Doppler ultrasound. Each fetal monitoring method has its advantages as well as disadvantages, and it should be emphasized that, regarding long-term measurements, a 20-min measurement is relatively short in order to obtain real information about the condition of the fetus.…”

Section: Introductionmentioning

confidence: 99%

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Jaroš

Martínek

Kahánková

2018

Sensors

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Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

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Non-Adaptive Methods of Fetal ECG Signal Processing

Cited by 23 publications

References 0 publications

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

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

Diagnostic approach in assessment of a ferroresonant circuit

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

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