Heartbeat detection from single-lead ECG contaminated with simulated EMG at different intensity levels: A comparative study

[1]  Abdelhamid Daamouche,et al.  A robust QRS detection approach using stationary wavelet transform , 2021, Multimedia Tools and Applications.

[2]  Ashish Kumar,et al.  Stationary wavelet transform based ECG signal denoising method. , 2020, ISA transactions.

[3]  Amirmasoud Ahmadi,et al.  Automated detection of driver fatigue from electroencephalography through wavelet-based connectivity , 2020 .

[4]  R. Buchhorn,et al.  Diagnosis and management of an inappropriate sinus tachycardia in adolescence based upon a Holter ECG: A retrospective analysis of 479 patients , 2020, PloS one.

[5]  Atul Kumar Dwivedi,et al.  Noise Reduction in ECG Signal Using Combined Ensemble Empirical Mode Decomposition Method with Stationary Wavelet Transform , 2020, Circuits Syst. Signal Process..

[6]  Luigi Raffo,et al.  Wavelet denoising as a post-processing enhancement method for non-invasive foetal electrocardiography , 2020, Comput. Methods Programs Biomed..

[7]  Amit Banerjee,et al.  An Efficient Porcine Acoustic Signal Denoising Technique Based on EEMD-ICA-WTD , 2019, Mathematical Problems in Engineering.

[8]  W. Frishman,et al.  The Clinical Value of Heart Rate Monitoring Using an Apple Watch , 2019, Cardiology in review.

[9]  Susmita Das,et al.  An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filter , 2018, Biomed. Signal Process. Control..

[10]  Dilbag Singh,et al.  Quantification of Feto-Maternal Heart Rate from Abdominal ECG Signal Using Empirical Mode Decomposition for Heart Rate Variability Analysis , 2017 .

[11]  Gilberto Perpinan,et al.  Data-Driven ECG Denoising Techniques for Characterising Bipolar Lead Sets along the Left Arm in Wearable Long-Term Heart Rhythm Monitoring , 2017 .

[12]  Lazar Saranovac,et al.  Algorithm for EMG noise level approximation in ECG signals , 2017, Biomed. Signal Process. Control..

[13]  B. Lin,et al.  Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview , 2017 .

[14]  Olaf Dössel,et al.  P wave detection and delineation in the ECG based on the phase free stationary wavelet transform and using intracardiac atrial electrograms as reference , 2016, Biomedizinische Technik. Biomedical engineering.

[15]  Abdelmalik Taleb-Ahmed,et al.  R-peaks detection based on stationary wavelet transform , 2015, Comput. Methods Programs Biomed..

[16]  Adrian D. C. Chan,et al.  Identification of Contaminant Type in Surface Electromyography (EMG) Signals , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[17]  Patrizia Vergallo,et al.  Empirical Mode Decomposition vs. Wavelet Decomposition for the Extraction of Respiratory Signal From Single-Channel ECG: A Comparison , 2013, IEEE Sensors Journal.

[18]  F. Bereksi-Reguig,et al.  Detection of QRS Complexes in ECG Signals Based on Empirical Mode Decomposition , 2011 .

[19]  Sabine Van Huffel,et al.  Source Separation From Single-Channel Recordings by Combining Empirical-Mode Decomposition and Independent Component Analysis , 2010, IEEE Transactions on Biomedical Engineering.

[20]  Sylvain Chartier,et al.  An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms , 2010 .

[21]  Steve McLaughlin,et al.  Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding , 2009, IEEE Transactions on Signal Processing.

[22]  S. Cerutti,et al.  Automatic screening of obstructive sleep apnea from the ECG based on empirical mode decomposition and wavelet analysis , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Pablo Laguna,et al.  A wavelet-based ECG delineator: evaluation on standard databases , 2004, IEEE Transactions on Biomedical Engineering.

[24]  S. T. Hamde,et al.  Feature extraction from ECG signals using wavelet transforms for disease diagnostics , 2002, Int. J. Syst. Sci..

[25]  H. Huikuri,et al.  Sudden death due to cardiac arrhythmias. , 2001, The New England journal of medicine.

[26]  G.B. Moody,et al.  The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.

[27]  R Merletti,et al.  Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[28]  W.J. Tompkins,et al.  ECG beat detection using filter banks , 1999, IEEE Transactions on Biomedical Engineering.

[29]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[30]  R. Scott,et al.  A Nonstationary Model for the Electromyogram , 1977, IEEE Transactions on Biomedical Engineering.

[31]  Ki H. Chon,et al.  An Accurate QRS Complex and P Wave Detection in ECG Signals Using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Approach , 2019, IEEE Access.

[32]  Madhuchhanda Mitra,et al.  Empirical mode decomposition based ECG enhancement and QRS detection , 2012, Comput. Biol. Medicine.

[33]  N. Abdolmaleki,et al.  SOURCE SEPARATION FROM SINGLE CHANNEL BIOMEDICAL SIGNAL BYCOMBINATION OF BLIND SOURCE SEPARATION AND EMPIRICAL MODE DECOMPOSITION , 2012 .

[34]  Norden E. Huang,et al.  Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method , 2009, Adv. Data Sci. Adapt. Anal..