Fetal Electrocardiogram Analysis Based on LMS Adaptive Filtering and Complex Continuous Wavelet 1-D

Ziani, Said; Hassouani, Y. El

doi:10.1007/978-3-030-23672-4_26

Cited by 20 publications

(7 citation statements)

References 6 publications

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“…This also appears to be applicable to synchronous motors using wavelets packets [48]- [49]. This study's findings also emphasize the need to use wavelets [50]- [52], integrated with data analysis techniques often employed in biomedical signal processing, such as ICA-NMF-SVD-PCA [53], [54] to further improve the aforementioned techniques' efficacy.…”

Section: Resultsmentioning

confidence: 64%

Solar panels overheating protection: a review

Laabab

Ziani

Benami

2022

IJEECS

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Reduced energy consumption is a direct result of building optimization. Solar panels and heat detectors can provide the necessary power. After years of refinement and development, methods for regulating solar panels' output are finally finding their way into everyday life, where they are having a dramatic impact on the foundations of sustainability. This document provides an up-to-date assessment of several strategies for preventing solar panels from overheating, all of which serve to boost their efficiency and prolong their service life. It begins with a brief background on protection technologies before moving on to a survey of recently filed patent applications that address this topic. The study concludes with a proposed assessment of the strengths and shortcomings of these safeguards. We anticipate that the information included in this review paper will be an invaluable tool for scholars and researchers.

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Section: Resultsmentioning

confidence: 64%

Solar panels overheating protection: a review

Laabab

Ziani

Benami

2022

IJEECS

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“…A comparison of the performance of several ICA based methods was performed in [82]. The LMS filter in combination with WT was used to extract the fECG efficiently in [59], [85]. The combination of LMS and ICA also achieved promising results in [70].…”

Section: B Methods For Fecg Signal Extractionmentioning

confidence: 99%

Non-Invasive Fetal Electrocardiogram Extraction Based on Novel Hybrid Method for Intrapartum ST Segment Analysis

et al. 2021

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This study focuses on non-invasive fetal electrocardiogram extraction based on a novel hybrid method, which combines the advantages of non-adaptive and adaptive approaches for non-invasive fetal electrocardiogram morphological analysis. Besides estimating fetal heart rate, which is the main parameter used in the clinical practice, this study provides non-invasive ST segment analysis on data from Abdominal and Direct Fetal Electrocardiogram Database consisting of simultaneous traditionalgold standard invasive fetal scalp electrode and non-invasive fetal electrocardiogram recorded during delivery. This innovative approach utilizing the combination of independent component analysis and recursive least squares algorithms has the potential to extract valuable information from non-invasive fetal electrocardiogram in order to identify eventual sign of fetal distress. This was a prospective observational study of non-invasive fetal electrocardiogram, using 4 abdominally sited electrodes, against the traditional fetal scalp electrode on 8 patients. In terms of fetal heart rate estimation, the accuracy was high for all 8 tested patients with average value equaled 0.20 beats per minute and average value of 1.96 standard deviation equaled 5.80 beats per minute. In 7 patients, it was possible to perform the ST segment analysis with high accuracy in determining T/QRS in comparison with the reference fetal scalp electrode signal with average values and 1.96 standard deviation equaled 0.008 and 0.031 respectively. This study thus demonstrates that ST segment analysis is feasible using non-invasive fECG using the proposed hybrid method. INDEX TERMS Non-invasive fetal electrocardiography (NI-fECG), fetal heart rate (fHR), ST segment analysis (ST-analysis), hybrid method (HM), independent component analysis and recursive least squares (ICA-RLS), electronic fetal monitoring (EFM), fetal distress (FD), fetal scalp electrode (FSE).

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“…Other methods of adaptive noise cancellation are least mean square (LMS) and Widrow's multireference [29][30][31]. On the other hand, techniques based on wavelet transforms (WT) [22,[32][33][34], empirical mode decomposition (EMD) [18,19,35], Kalman filtering [25,36], artificial neural networks [37][38][39], adaptative filtering [40][41][42], blind source separation [7,26,30,43], or even clustering-based algorithms [14], have been shown to be useful in the extraction of components more suitable to obtain relevant characteristics of the fECG, such as R-peak locations. The techniques to denoise aECG signals and to extract reliable fetus information used in this work are summarized in the following.…”

Section: Processing Of Ni-fecgmentioning

confidence: 99%

PCA-Based Preprocessing for Clustering-Based Fetal Heart Rate Extraction in Non-Invasive Fetal Electrocardiograms

Oyarzún,

Castillo,

Parrilla

et al. 2024

Electronics

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Non-invasive fetal electrocardiography (NI-ECG) is based on the acquisition of signals from electrodes on the mother’s abdominal surface. This abdominal ECG (aECG) signal consists of the maternal ECG (mECG) along with the fetal ECG (fECG) and other noises and artifacts. These records allow the acquisition of valuable and reliable information that helps ensure fetal well-being during pregnancy. This paper proposes a procedure based on principal component analysis (PCA) to obtain a single-channel master abdominal ECG record that can be used as input to fetal heart rate extraction techniques. The new procedure requires three main processing stages: PCA-based analysis for fECG-component extraction, polarity test, and curve fitting. To show the advantages of the proposal, this PCA-based method has been used as the feeding stage to a previously developed clustering-based method for single-channel aECG fetal heart rate monitoring. The results obtained for a set of real abdominal ECG recordings from annotated public aECG databases, the Abdominal and Direct Fetal ECG Database and the Challenge 2013 Training Set A, show improved efficiency in fetal heart rate extraction and illustrate the benefits derived from the use of such a master abdominal ECG channel. This allows us to achieve proper fetal heart rate monitoring without the need for manual inspection and selection of channels to be processed, while also allowing us to analyze records that would have been discarded otherwise.

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Fetal Electrocardiogram Analysis Based on LMS Adaptive Filtering and Complex Continuous Wavelet 1-D

Cited by 20 publications

References 6 publications

Solar panels overheating protection: a review

Solar panels overheating protection: a review

Non-Invasive Fetal Electrocardiogram Extraction Based on Novel Hybrid Method for Intrapartum ST Segment Analysis

PCA-Based Preprocessing for Clustering-Based Fetal Heart Rate Extraction in Non-Invasive Fetal Electrocardiograms

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