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Relevant bibliographies by topics / FECG EXTRACTION

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Academic literature on the topic 'FECG EXTRACTION'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "FECG EXTRACTION"

1

Hao, Jingyu, Yuyao Yang, Zhuhuang Zhou, and Shuicai Wu. "Fetal Electrocardiogram Signal Extraction Based on Fast Independent Component Analysis and Singular Value Decomposition." Sensors 22, no. 10 (2022): 3705. http://dx.doi.org/10.3390/s22103705.

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Fetal electrocardiograms (FECGs) provide important clinical information for early diagnosis and intervention. However, FECG signals are extremely weak and are greatly influenced by noises. FECG signal extraction and detection are still challenging. In this work, we combined the fast independent component analysis (FastICA) algorithm with singular value decomposition (SVD) to extract FECG signals. The improved wavelet mode maximum method was applied to detect QRS waves and ST segments of FECG signals. We used the abdominal and direct fetal ECG database (ADFECGDB) and the Cardiology Challenge Da

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2

K., Ricky, Arjuna M, and Sadegh Aminifar. "Fetal Heart Rate Extraction using NLMS Algorithm." International Journal of Biology and Biomedical Engineering 15 (April 7, 2021): 61–67. http://dx.doi.org/10.46300/91011.2021.15.8.

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This project develops a fetal heart rate (FHR) extraction application to analyze the fetus activity in the mother uterus. Several methods are available that can be used to detect FHR such as using the fetal electrocardiogram (FECG) that generated by fetus’ heart. Extracting FECG signals is considered a major challenge while the fetus is inside the mother uterus. Normalized Least Mean Square (NLMS) algorithm is one of adaptive filters that is chosen as adaptive filter to get FECG. Pan Tompkins algorithm is used for tracking R-peaks of heartbeat pulses of FECG signal. After detecting the RR inte

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3

Taha, Luay, and Esam Abdel-Raheem. "A Null Space-Based Blind Source Separation for Fetal Electrocardiogram Signals." Sensors 20, no. 12 (2020): 3536. http://dx.doi.org/10.3390/s20123536.

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This paper presents a new non-invasive deterministic algorithm of extracting the fetal Electrocardiogram (FECG) signal based on a new null space idempotent transformation matrix (NSITM). The mixture matrix is used to compute the ITM. Then, the fetal ECG (FECG) and maternal ECG (MECG) signals are extracted from the null space of the ITM. Next, MECG and FECG peaks detection, control logic, and adaptive comb filter are used to remove the unwanted MECG component from the raw FECG signal, thus extracting a clean FECG signal. The visual results from Daisy and Physionet real databases indicate that t

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4

Liao, Qiong, Jie Luo, and Yang Liu. "Fetal Electrocardiogram Extraction Based on SWT-MM Method." Applied Mechanics and Materials 644-650 (September 2014): 4415–21. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.4415.

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Fetal electrocardiogram (FECG) is of great importance due to the potentially precise information that FECG carries could assist clinicians in making more appropriate and timely decisions during pregnancy and labor. In this paper, a method based on combined Stationary Wavelet Transform and Modulus-Maxima (SWT-MM) method is proposed for extracting the complete morphology of the FECG from maternal abdominal ECG (AECG). It particularly provides a different way of constructing the maternal ECG (MECG) template. The Efficacy of the method was validated using real data in Non-Invasive Fetal Electrocar

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5

Graupe, D., M. H. Graupe, Y. Zhong, and R. K. Jackson. "Blind adaptive filtering for non-invasive extraction of the fetal electrocardiogram and its non-stationarities." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 222, no. 8 (2008): 1221–34. http://dx.doi.org/10.1243/09544119jeim417.

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The objective is to extract automatically a beat-to-beat fetal electrocardiogram (fECG) from a maternal electrocardiogram (mECG) using surface electrodes placed on the maternal abdomen and to derive fetal PR, QT, QTc, and QS durations to allow early diagnosis and monitoring treatment of certain fetal cardiac disorders. mECG and abdominal noise in abdominal maternal recordings can be orders of magnitude stronger than the fECG signal and the P and T waves that are embedded in them. A two-stage blind adaptive filtering algorithm was used for fECG extraction, the first stage using frequency-domain

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6

Li, Rui, and Bao Feng Chen. "FECG Extraction Algorithm Based on BSS Using Temporal Structure and DWT." Applied Mechanics and Materials 571-572 (June 2014): 209–12. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.209.

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Fetal electrocardiogram (FECG) blind source extraction (BSE) algorithm based on temporal structure and discrete wavelet transformation (DWT) in noise is proposed in this paper. After building the basic blind source separation (BSS) and BSE models for FECG, some preprocessing procedures based on the temporal structure of the FECG are constructed. Using DWT we can move the conventional time-domain signals to the wavelet-domain, and then the source number is detected and the robust noise reduction technique in FECG can be deduced too. According this preprocessing and second-order statistics (SOS)

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7

Li, Yibing, Wei Nie, Fang Ye, and Ao Li. "A Fetal Electrocardiogram Signal Extraction Algorithm Based on the Temporal Structure and the Non-Gaussianity." Computational and Mathematical Methods in Medicine 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/9658410.

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Fetal electrocardiogram (FECG) extraction is an important issue in biomedical signal processing. In this paper, we develop an objective function for extraction of FECG. The objective function is based on the non-Gaussianity and the temporal structure of source signals. Maximizing the objective function, we can extract the desired FECG. Combining with the solution vector obtained by maximizing the objective function, we further improve the accuracy of the extracted FECG. In addition, the feasibility of the innovative methods is analyzed by mathematical derivation theoretically and the efficienc

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8

Zhang, Miao, and Guo Wei. "An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction." Applied Sciences 10, no. 16 (2020): 5634. http://dx.doi.org/10.3390/app10165634.

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In this paper, an instantaneous correlation coefficient and simplified coherent averaging method for single-channel foetal ECG (FECG) extraction is proposed. The instantaneous correlation coefficient is used to determine the position of the R peak of the measured ECG signal, and the simplified coherent averaging method is used to extract the main information of the ECG signal. The loss of the nonlinear and nonstationary characteristics by coherent averaging is recovered by threshold processing of the residual signal. The FECG signal extraction is performed in three steps. In the first step, th

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9

Mohsen Alkanfery, Hadi, and Ibrahim Mustafa Mehedi. "Fractional Order Butterworth Filter for Fetal Electrocardiographic Signal Feature Extraction." Signal & Image Processing : An International Journal 12, no. 05 (2021): 45–56. http://dx.doi.org/10.5121/sipij.2021.12503.

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The non-invasive Fetal Electrocardiogram (FECG) signal has become a significant method for monitoring the fetus's physiological conditions, extracted from the Abdominal Electrocardiogram (AECG) during pregnancy. The current techniques are limited during delivery for detecting and analyzing fECG. The non - intrusive fECG recorded from the mother's abdomen is contaminated by a variety of noise sources, can be a more challenging task for removing the maternal ECG. These contaminated noises have become a major challenge during the extraction of fetal ECG is managed by uni-modal technique. In this

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10

Sarafan, Sadaf, Tai Le, Michael P. H. Lau, Afshan Hameed, Tadesse Ghirmai, and Hung Cao. "Fetal Electrocardiogram Extraction from the Mother’s Abdominal Signal Using the Ensemble Kalman Filter." Sensors 22, no. 7 (2022): 2788. http://dx.doi.org/10.3390/s22072788.

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Fetal electrocardiogram (fECG) assessment is essential throughout pregnancy to monitor the wellbeing and development of the fetus, and to possibly diagnose potential congenital heart defects. Due to the high noise incorporated in the abdominal ECG (aECG) signals, the extraction of fECG has been challenging. And it is even a lot more difficult for fECG extraction if only one channel of aECG is provided, i.e., in a compact patch device. In this paper, we propose a novel algorithm based on the Ensemble Kalman filter (EnKF) for non-invasive fECG extraction from a single-channel aECG signal. To ass

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