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Journal articles on the topic 'FECG EXTRACTION'

Author: Grafiati

Published: 11 September 2023

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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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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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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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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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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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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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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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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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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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Mertes, Gert, Yuan Long, Zhangdaihong Liu, Yuhui Li, Yang Yang, and David A. Clifton. "A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography." Sensors 22, no. 9 (2022): 3303. http://dx.doi.org/10.3390/s22093303.

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Non-invasive foetal electrocardiography (NI-FECG) has become an important prenatal monitoring method in the hospital. However, due to its susceptibility to non-stationary noise sources and lack of robust extraction methods, the capture of high-quality NI-FECG remains a challenge. Recording waveforms of sufficient quality for clinical use typically requires human visual inspection of each recording. A Signal Quality Index (SQI) can help to automate this task but, contrary to adult ECG, work on SQIs for NI-FECG is sparse. In this paper, a multi-channel signal quality classifier for NI-FECG wavef

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Sivaraman, Himani. "Application of SVM Algorithm for Fetal ECG Extraction from a Single Maternal Abdominal Record." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, no. 1 (2019): 638–44. http://dx.doi.org/10.17762/turcomat.v10i1.13560.

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The electrical activity of the foetal cardiac muscles is known as foetal ECG (FECG), and it can provide crucial details on the health of the fetus's heart. A pregnant woman's belly can be used to non-invasively capture this signal during pregnancy. However, since additional sources of noise, including the maternal ECG generally overpower the FECG recording, it would be ineffective. However, a clean FECG may be retrieved from the abdominal recording if it is correctly processed, and FECG can be used to evaluate the functioning of the foetal heart. In order to extract foetal electrocardiogram (E

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Praneeth, CH N. V. S., Jaba Deva Krupa Abel, Dhanalakshmi Samiappan, R. Kumar, S. Pravin Kumar, and Patnala Venkat Nitin. "A COMPARISON ON VARIANTS OF LMS USED IN FIR ADAPTIVE NOISE CANCELLERS FOR FETAL ECG EXTRACTION." Biomedical Engineering: Applications, Basis and Communications 32, no. 04 (2020): 2050026. http://dx.doi.org/10.4015/s101623722050026x.

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Fetal electrocardiogram (FECG) non-invasively obtained through abdominal recordings serves as a promising diagnostic tool for fetal health monitoring during pregnancy. However, in the abdominal ECG (AECG) signal, FECG overlaps with maternal ECG (MECG) in both temporal and spectral domains in addition to interference from various sources like electromyogram, electrogastrogram, motion artifacts and other noises. The objective of this paper is to eliminate MECG components from AECG signal to extract FECG signal through FIR adaptive noise canceller (ANC) with filter coefficients updated using adap

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Jallouli, Malika, Sabrine Arfaoui, Anouar Ben Mabrouk, and Carlo Cattani. "Clifford Wavelet Entropy for Fetal ECG Extraction." Entropy 23, no. 7 (2021): 844. http://dx.doi.org/10.3390/e23070844.

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Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the fetal ECG from the mother ECG during pregnancy. This approach has the advantage of being a reliable and non-invasive technique. In the present paper, a wavelet/multiwavelet method is proposed to perfectly extract the fetal ECG parameters from the abdominal mother ECG. In a first step

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Al-Sheikh, Bahaa, Mohammad Shukri Salman, Alaa Eleyan, and Shadi Alboon. "Non-invasive fetal ECG extraction using discrete wavelet transform recursive inverse adaptive algorithm." Technology and Health Care 28, no. 5 (2020): 507–20. http://dx.doi.org/10.3233/thc-191948.

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BACKGROUND: Fetal heart activity adds significant information about the status of the fetus health. Early diagnosis of issues in the heart before delivery allows early intervention and significantly improves the treatment. OBJECTIVE: This paper presents a new adaptive filtering algorithm for fetal electrocardiogram (FECG) extraction from the maternal abdominal signal, known in literature as abdominal electrocardiogram (AECG) signal. Fetal QRS complex waves will be identified and extracted accurately for fetal health care and monitoring purposes. METHODS: We use discrete wavelet transform recur

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Jia, Yanfei, and Xiaodong Yang. "A Fetal Electrocardiogram Signal Extraction Algorithm Based on Fast One-Unit Independent Component Analysis with Reference." Computational and Mathematical Methods in Medicine 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/5127978.

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Fetal electrocardiogram (FECG) extraction is very important procedure for fetal health assessment. In this article, we propose a fast one-unit independent component analysis with reference (ICA-R) that is suitable to extract the FECG. Most previous ICA-R algorithms only focused on how to optimize the cost function of the ICA-R and payed little attention to the improvement of cost function. They did not fully take advantage of the prior information about the desired signal to improve the ICA-R. In this paper, we first use the kurtosis information of the desired FECG signal to simplify the non-G

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Sarafan, Sadaf, Tai Le, Amir Mohammad Naderi, et al. "Investigation of Methods to Extract Fetal Electrocardiogram from the Mother’s Abdominal Signal in Practical Scenarios." Technologies 8, no. 2 (2020): 33. http://dx.doi.org/10.3390/technologies8020033.

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Monitoring of fetal electrocardiogram (fECG) would provide useful information about fetal wellbeing as well as any abnormal development during pregnancy. Recent advances in flexible electronics and wearable technologies have enabled compact devices to acquire personal physiological signals in the home setting, including those of expectant mothers. However, the high noise level in the daily life renders long-entrenched challenges to extract fECG from the combined fetal/maternal ECG signal recorded in the abdominal area of the mother. Thus, an efficient fECG extraction scheme is a dire need. In

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Awan, Muhammad Tayyib, Muhammad Amir, Sarmad Maqsood, Musyyab Yousufi, Suheel Abdullah, and MUHAMMAD IRFAN. "Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component." Information Technology and Control 50, no. 1 (2021): 123–37. http://dx.doi.org/10.5755/j01.itc.50.1.24145.

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Fetal ECG extraction from abdominal ECG is critical task for telemonitoring of fetus which require lot of understanding to the subject. Conventional source separation methods are not efficient enough to separate FECG from huge multichannel ECG. Thus use of compression technique is needed to compress and reconstruct ECG signal without any significant losses in quality of signal. Compressed sensing shows promising results for such tasks. However, current compressed sensing theory is not so far that successful due to the non-sparsity and strong noise contamination present in ECG signal. The propo

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Ţarălungă, Dragoş-Daniel, Georgeta-Mihaela Ungureanu, Ilinca Gussi, Rodica Strungaru, and Werner Wolf. "Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics." Computational and Mathematical Methods in Medicine 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/239060.

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Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods

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Haq, Tashreque Mohammed, Safkat Arefin, Shamiur Rahman, and Tanzilur Rahman. "Extraction of Fetal Heart Rate from Maternal ECG—Non Invasive Approach for Continuous Monitoring during Labor." Proceedings 2, no. 13 (2018): 1009. http://dx.doi.org/10.3390/proceedings2131009.

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Here, we propose a signal processing based approach for the extraction of the fetal heart rate (FHR) from Maternal Abdominal ECG (MAECG) in a non-invasive way. Datasets from a Physionet database has been used in this study for evaluating the performance of the proposed model that performs three major tasks; preprocessing of the MAECG signal, separation of Fetal QRS complexes from that of maternal and estimation of Fetal R peak positions. The MAECG signal is first preprocessed with improved multistep filtering techniques to detect the Maternal QRS (MQRS) complexes, which are dominant in the MAE

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Cao, Shi, Hui Xiao, Gao Gong, Weiyang Fang, and Chaomin Chen. "Morphology extraction of fetal ECG using temporal CNN-based nonlinear adaptive noise cancelling." PLOS ONE 17, no. 12 (2022): e0278917. http://dx.doi.org/10.1371/journal.pone.0278917.

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Objectives Noninvasive fetal electrocardiography (FECG) offers many advantages over alternative fetal monitoring techniques in evaluating fetal health conditions. However, it is difficult to extract a clean FECG signal with morphological features from an abdominal ECG recorded at the maternal abdomen; the signal is usually contaminated by the maternal ECG and various noises. The aim of the work is to extract an FECG signal that preserves the morphological features from the mother’s abdominal ECG recording, which allows for accurately estimating the fetal heart rate (FHR) and analyzing the wave

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Ren, Dongxiao, Mao Ye, Ying Yin, and Yuanxiang Zhu. "FECG extraction from nonlinear mixture based on minimization of mutual information." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 24, no. 7 (2010): 680–85. http://dx.doi.org/10.3724/sp.j.1187.2010.00680.

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23

Vo, Khuong, Tai Le, Amir M. Rahmani, Nikil Dutt, and Hung Cao. "An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram." Sensors 20, no. 13 (2020): 3757. http://dx.doi.org/10.3390/s20133757.

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The invasive method of fetal electrocardiogram (fECG) monitoring is widely used with electrodes directly attached to the fetal scalp. There are potential risks such as infection and, thus, it is usually carried out during labor in rare cases. Recent advances in electronics and technologies have enabled fECG monitoring from the early stages of pregnancy through fECG extraction from the combined fetal/maternal ECG (f/mECG) signal recorded non-invasively in the abdominal area of the mother. However, cumbersome algorithms that require the reference maternal ECG as well as heavy feature crafting ma

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Yao, Wen Po, Jun Chang Zhao, Zheng Zhong Zheng, Tie Bing Liu, Hong Xing Liu, and Jun Wang. "Fetal Electrocardiogram Extraction Based on Modified Robust Independent Component Analysis." Advanced Materials Research 749 (August 2013): 250–53. http://dx.doi.org/10.4028/www.scientific.net/amr.749.250.

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Fetal electrocardiogram (FECG) separation gets widely attention due to its clinical significance. In the paper, we proposed an improved robust independent component analysis for fetal ECG separation. Firstly, wavelet decomposition was applied to fetal ECG to get the relevant parameters. Then, the RobustICA was used to separate the mixed signals. Compared to robust independent component analysis, computing speed of the improved algorithm increased by an average of 15 percent while minimum mean square error fluctuations 0.0008, which indicated that this algorithm could be effectively used in cli

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BAŞPINAR, Ulvi, and Yasemin KÖYLÜ. "DETECTION OF FETAL ELECTROCARDIOGRAM SIGNALS FROM MATERNAL ABDOMINAL ECG RECORDINGS." Journal of Scientific Reports-A, no. 052 (March 29, 2023): 266–78. http://dx.doi.org/10.59313/jsr-a.1173530.

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Fetal electrocardiogram (fECG) is a signal that contains vital information about the health of the fetus throughout pregnancy. During pregnancy, it is important to monitor and analyse this signal because it represents the electrical activity of the developing fetal heart. Early detection of fetal ECG problems during the fetus' development is crucial because it allows early treatment and provides knowledge about diseases that may emerge at a later time. Extraction of fetal ECG from the abdomen ECG signal is valuable in these aspects. In order to extract the fetal ECG from the recorded abdomen E

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Meddour, Cherif, and Malika Kedir-Talha. "NEW METHOD EXPLOITING A HYBRID TECHNIQUES FOR FETAL CARDIAC SIGNAL EXTRACTION." Biomedical Engineering: Applications, Basis and Communications 31, no. 04 (2019): 1950027. http://dx.doi.org/10.4015/s1016237219500273.

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According to WHO, 2.6 million babies die during pregnancy. Good monitoring during the prenatal period could provide a significant reduction of this mortality rate. This is possible by detection and extraction of the fetal electrocardiogram (FECG). Extraction of that information is complex due to other noise coming from the mother and within the fetus that drowns out the fetal heart signal. However, new technology and improved filtering technique have provided ways to more accurately and efficiently gather various electrical components regarding fetal heart condition. In this paper, we propose

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Swarnalath, R., and D. V. Prasad. "A Novel Technique for Extraction of FECG using Multi Stage Adaptive Filtering." Journal of Applied Sciences 10, no. 4 (2010): 319–24. http://dx.doi.org/10.3923/jas.2010.319.324.

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Vasudeva, Bhavya, Puneesh Deora, Pradhan Mohan Pradhan, and Sudeb Dasgupta. "Efficient implementation of LMS adaptive filter-based FECG extraction on an FPGA." Healthcare Technology Letters 7, no. 5 (2020): 125–31. http://dx.doi.org/10.1049/htl.2020.0016.

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Yu, Wei, Qiang Han, Jing Jing Ma, and Pei Xie. "A New Method for Biomedical Signal Processing with EMD and ICA Approach." Advanced Materials Research 546-547 (July 2012): 548–52. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.548.

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Faint signal extraction is always a difficult issue in biomedical signal processing field, because the desired signal is often submerged in several relatively large signals or noises. A novel faint signal processing method based on Empirical Mode Decomposition (EMD) and Independent Component Analysis (ICA) is developed to enhance the sensitivity and reliability of faint signal detection. This novel method includes two major steps, which is, firstly the decomposition of the biomedical composite signal using EMD, then the classification or extraction of the desired faint signal component through

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Zhang, Yuwei, Aihua Gu, Zhijun Xiao, et al. "Wearable Fetal ECG Monitoring System from Abdominal Electrocardiography Recording." Biosensors 12, no. 7 (2022): 475. http://dx.doi.org/10.3390/bios12070475.

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Fetal electrocardiography (ECG) monitoring during pregnancy can provide crucial information for assessing the fetus’s health status and making timely decisions. This paper proposes a portable ECG monitoring system to record the abdominal ECG (AECG) of the pregnant woman, comprising both maternal ECG (MECG) and fetal ECG (FECG), which could be applied to fetal heart rate (FHR) monitoring at the home setting. The ECG monitoring system is based on data acquisition circuits, data transmission module, and signal analysis platform, which consists of low input-referred noise, high input impedance, an

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Karvounis, E. C., M. G. Tsipouras, C. Papaloukas, D. G. Tsalikakis, K. K. Naka, and D. I. Fotiadis. "A Non-invasive Methodology for Fetal Monitoring during Pregnancy." Methods of Information in Medicine 49, no. 03 (2010): 238–53. http://dx.doi.org/10.3414/me09-01-0041.

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Summary Objectives: This paper describes a methodology for the monitoring of the fetal cardiac health status during pregnancy, through the effective and non-invasive monitoring of the abdominal ECG signals (abdECG) of the mother. Methods: For this purpose, a three-stage methodology has been developed. In the first stage, the fetal heart rate (fHR) is extracted from the abdECG signals, using nonlinear analysis. Also, the eliminated ECG (eECG) is calculated, which is the abdECG after the maternal QRSs elimination. In the second stage, a blind source separation technique is applied to the eECG si

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Kahankova, Radana, Martina Mikolasova, and Radek Martinek. "Optimization of adaptive filter control parameters for non-invasive fetal electrocardiogram extraction." PLOS ONE 17, no. 4 (2022): e0266807. http://dx.doi.org/10.1371/journal.pone.0266807.

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This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters of different hybrid systems used for non-invasive fetal electrocardiogram (fECG) extraction. The tested hybrid systems consist of two different blocks, first for maternal component estimation and second, so-called adaptive block, for maternal component suppression by means of an adaptive algorithm (AA). Herein, we tested and optimized four different AAs: Adaptive Linear Neuron (ADALINE), Standard Least Mean Squares (LMS), Sign-Error LMS, Standard Recursive Least

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Putra, Darma Setiawan, and Yuril Umbu WW. "Feature Extraction of Facial Electromyograph (EMG) Signal for Aceh Languages Speech using Discrete Wavelet Transform (DWT)." Jurnal Inotera 4, no. 1 (2019): 31. http://dx.doi.org/10.31572/inotera.vol4.iss1.2019.id73.

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The facial electromyograph (FEMG) signal is a signal that occurs in the muscles of the contracted human face. This FEMG signal is one of the techniques used to study human speech recognition. It can be acquired by placing an electrode surface on the skin around the facial articulation muscle. Three types of muscles in this study are the masseter, risorius and depressor muscle. This study aims to extract and analyze the features in the FEMG signal. The extraction method is the discrete wavelet transform (DWT). The type of wavelet transform is Daubechies2 with level 5. After extraction and analy

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Zhou, Heng Yan, Yu Cong Xu, Yu Xi Luo, and Yu Bao Gao. "Optimizing the Algorithm of FECG Separation from MECG Based on ICA Rationale." Advanced Materials Research 846-847 (November 2013): 1257–61. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1257.

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The study presents a method to separate the fetal electrocardiograph (FECG) from concomitant maternal electrocardiograph (MECG) by using Fast Independent component analysis (ICA) algorithm of Blind Signal Separation. Current methods of extracting fetal ECG have defects and drawbacks. Traditional ICA method has a persistent problem that the signal of FECG extracted from MECG was always mixed with the signal of MECG in diverse levels, and the order of MECG and FECG is uncertain, resulting in the decrease of its rate of convergence. To improve the rate of convergence, this research adopts Fast IC

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Keenan, Emerson, Chandan Karmakar, Radhagayathri K. Udhayakumar, et al. "Detection of fetal arrhythmias in non-invasive fetal ECG recordings using data-driven entropy profiling." Physiological Measurement 43, no. 2 (2022): 025008. http://dx.doi.org/10.1088/1361-6579/ac4e6d.

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Abstract Objective. Fetal arrhythmias are a life-threatening disorder occurring in up to 2% of pregnancies. If identified, many fetal arrhythmias can be effectively treated using anti-arrhythmic therapies. In this paper, we present a novel method of detecting fetal arrhythmias in short length non-invasive fetal electrocardiography (NI-FECG) recordings. Approach. Our method consists of extracting a fetal heart rate time series from each NI-FECG recording and computing an entropy profile using a data-driven range of the entropy tolerance parameter r. To validate our approach, we apply our entrop

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Nezhadali, A., Z. Es’haghi, and A. Khatibi. "Selective extraction of progesterone hormones from environmental and biological samples using a polypyrrole molecularly imprinted polymer and determination by gas chromatography." Analytical Methods 8, no. 8 (2016): 1813–27. http://dx.doi.org/10.1039/c5ay02174j.

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Li, Xiaohua, Wouter Monnens, Zheng Li, Jan Fransaer, and Koen Binnemans. "Solvometallurgical process for extraction of copper from chalcopyrite and other sulfidic ore minerals." Green Chemistry 22, no. 2 (2020): 417–26. http://dx.doi.org/10.1039/c9gc02983d.

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Lee, Man-Seung, Gwang-Seop Lee, and Keun Yong Sohn. "Solvent Extraction Equilibria of FeCl₃ with TBP." MATERIALS TRANSACTIONS 45, no. 6 (2004): 1859–63. http://dx.doi.org/10.2320/matertrans.45.1859.

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Babaee, Shirin, and Ali Daneshfar. "Magnetic deep eutectic solvent-based ultrasound-assisted liquid–liquid microextraction for determination of hexanal and heptanal in edible oils followed by gas chromatography–flame ionization detection." Analytical Methods 10, no. 34 (2018): 4162–69. http://dx.doi.org/10.1039/c8ay01058g.

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Use of a novel magnetic deep eutectic solvent (MDES), consisting of the inexpensive and simple components [choline chloride/para-cresol] [FeCl<sub>4</sub>] was examined using ultrasound-assisted liquid–liquid microextraction and back-extraction methods to determine hexanal and heptanal in edible oils.

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Hao, Yun, Ying-juan Hao, Jie Ren, et al. "Extractive/catalytic oxidative mechanisms over [Hnmp]Cl·xFeCl3 ionic liquids towards the desulfurization of model oils." New Journal of Chemistry 43, no. 20 (2019): 7725–32. http://dx.doi.org/10.1039/c9nj00691e.

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Wang, Yong, Andrey Karasev, and Pär G. Jönsson. "An Investigation of Non-Metallic Inclusions in Different Ferroalloys using Electrolytic Extraction." Metals 9, no. 6 (2019): 687. http://dx.doi.org/10.3390/met9060687.

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Ferroalloys are integral constituents of the steelmaking process, since non-metallic inclusions (NMIs) from ferroalloys significantly influence the transformation of inclusions present in liquid steel or they are directly involved in casted steel. In this study, the characteristics of inclusions (such as the number, morphology, size, and composition) in different industrial ferroalloys (FeV, FeMo, FeB, and FeCr) were investigated using the electrolytic extraction (EE) technique. After extraction from the ferroalloy samples and filtration of the solution, the inclusions were investigated on a f

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Коплак, О. В., В. Л. Сидоров, Е. И. Куницына та ін. "Бистабильное и многодоменное состояния ферромагнитных микропроводов alpha-Fe/(PrDy)(FeCo)B". Физика твердого тела 61, № 11 (2019): 2090. http://dx.doi.org/10.21883/ftt.2019.11.48412.524.

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Microwire of α-Fe(50 at.%)(PrDy)(FeCo)B(48 at.%) was obtained by extracting a hanging melt drop of (PrDy)(FeCo)B in an electron beam. It was shown that a single microwire with a diameter of 50 μm and a length of 0.8 - 6 mm with an amorphous phase (PrDy)(FeCo)B content of ~ 48% and a polycrystalline α-Fe phase of ~ 52% has a rectangular narrow magnetic hysteresis loop and, accordingly, a bistable state with a switching field of ~ 100 Oe. The shortening of the wire to ~ 0.6 mm leads to a sharp deviation from the squareness of the loop, reducing the slope of the dependence of the magnetization on

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Li, Wei Guang, Ke Li Chen, and Hu Hua Liu. "Research on Technology of Gas Drainage in Highly Gassy and Thin Coal Seams with Long Wall Coal Face on the Strike." Advanced Materials Research 807-809 (September 2013): 2450–54. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.2450.

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Based on the Feng Huang Coalmine 1402# coalface, applying the vertical three zones of overlying strata theory and O-ring theory, this paper discusses the migration paths of pressure-relieved gas in stope and the abundant gas region. By means of optimizing the roof crossing borehole method and high-position borehole in gob method, the gas drainage efficiency and extraction concentration have been improved, the gas emission arising from coalface has been reduced, and the gas accumulation phenomenon has been eliminated, which verifies the accuracy of this research and realizes the safe and effici

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Mauro Mirto, Ignazio. "Automatic Extraction of Semantic Roles in Support Verb Constructions." International Journal on Natural Language Computing 10, no. 03 (2021): 1–10. http://dx.doi.org/10.5121/ijnlc.2021.10301.

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This paper deals with paraphrastic relations in Italian. In the following sentences: (a) Max strappò delle lacrime a Sara 'Max moved Sara to tears' and (b) Max fece piangere Sara 'Max made Sara cry', the verbs differ syntactically and semantically. Strappare 'tear/rip/wring' is transitive, fare ‘have/make’ is a causative, and piangere 'cry' is intransitive. Despite this, a translation of (a) as (b) is legitimate and therefore (a) is a paraphrase of (b). In theoretical linguistics this raises an issue concerning the relationship between strappare and fare/piangere in Italian, and that in Englis

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Jaros, Rene, Katerina Barnova, Radana Vilimkova Kahankova, Jan Pelisek, Martina Litschmannova, and Radek Martinek. "Independent component analysis algorithms for non-invasive fetal electrocardiography." PLOS ONE 18, no. 6 (2023): e0286858. http://dx.doi.org/10.1371/journal.pone.0286858.

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The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms. However, there are many variants of the ICA methods and it is not clear which one is the most suitable for this task. The goal of this study is to test and objectively evaluate 11 variants of ICA methods combined with an adaptive fast transversal filter (FTF) for the purpose of extracting the NI-fECG. The methods were tested on two datasets, Labour datase

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Takahashi, Gen. "Tannin-ferrocyanide OsO4 method for scanning electron microscopy with use of microwave irradiation." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 3 (1990): 26–27. http://dx.doi.org/10.1017/s0424820100157668.

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The disadvantages of metal-coating techniques in high resolution SEM are limitation of resolution due to the thickness of coating, metal decoration of the surface ultrastructures, the lack of uniformity and continuity of coating or specimen damage during coating due to heat generation. In order to overcome these disadvantages and to obtain the better ultrastructural preservation after drying of specimens, the conductive staining methods have been devised.˜4The microwave irradiation(MWI) has recently been used for fixation of biological specimens for light and electron microscopy, immunohistoch

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Joy, David C. "Microanalysis with a 200keV FEG TEM." Proceedings, annual meeting, Electron Microscopy Society of America 49 (August 1991): 700–701. http://dx.doi.org/10.1017/s0424820100087811.

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Introduction The Hitachi HF-2000 is a 200keV cold field emitter TEM, designed to offer both high resolution imaging performance and a nanometer probe-forming mode for microanalytical operation. The purpose of this paper is to report some initial microanalytical results obtained from the HF-2000 installed at the University of Tennessee.General Electron-Optical Parameters The cold field emission gun, which runs at about 5x10-9pA pressure, uses an electrostatic lens configuration and a six stage accelerator. The entire electron gun system is under the control of a dedicated microprocessor which p

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Lee, Man-Seung, Kyoung-Ju Lee, and Young-Joo Oh. "Solvent Extraction Equilibria of FeCl₃ from Hydrochloric Acid Solution with Alamine336." MATERIALS TRANSACTIONS 45, no. 7 (2004): 2364–68. http://dx.doi.org/10.2320/matertrans.45.2364.

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Zheng, Hai-yan, Yu Sun, Jin-wen Lu, Jian-hong Dong, Wei-ling Zhang, and Feng-man Shen. "Vanadium extraction from vanadium-bearing titanomagnetite by selective chlorination using chloride wastes (FeCl x )." Journal of Central South University 24, no. 2 (2017): 311–17. http://dx.doi.org/10.1007/s11771-017-3432-x.

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Malallah, Yaaqoub, Antarpreet Singh, Sampada Deshmukh, Chins Chinnasamy, Melania Marinescu, and Afshin S. Daryoush. "Complex permeability extraction of FeCo nanoparticles using annular ring resonator and its RF applications." Journal of the Franklin Institute 354, no. 18 (2017): 8758–71. http://dx.doi.org/10.1016/j.jfranklin.2017.04.014.

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