Comparison of ECG fiducial point extraction methods based on dynamic Bayesian network
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Christian Jutten | Mahsa Akhbari | Mohammad B. Shamsollahi | C. Jutten | M. Shamsollahi | Mahsa Akhbari
[1] Mohammad B. Shamsollahi,et al. Fetal electrocardiogram R-peak detection using robust tensor decomposition and extended Kalman filtering , 2013, Computing in Cardiology 2013.
[2] M B Shamsollahi,et al. A model-based Bayesian framework for ECG beat segmentation , 2009, Physiological measurement.
[3] Christian Jutten,et al. Fiducial points extraction and characteristicwaves detection in ECG signal using a model-based bayesian framework , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[4] Geoffrey E. Hinton,et al. Switching State-Space Models , 1996 .
[5] Bernadette Dorizzi,et al. ECG signal analysis through hidden Markov models , 2006, IEEE Transactions on Biomedical Engineering.
[6] Christian Jutten,et al. ECG fiducial points extraction by extended Kalman filtering , 2013, 2013 36th International Conference on Telecommunications and Signal Processing (TSP).
[7] A. A. Armoundas,et al. ECG denoising and fiducial point extraction using an extended Kalman filtering framework with linear and nonlinear phase observations , 2016, Physiological measurement.
[8] Beverly C. Yu,et al. A Nonlinear Digital Filter For Cardiac QRS Complex Detection , 1985 .
[9] G.G. Cano,et al. An approach to cardiac arrhythmia analysis using hidden Markov models , 1990, IEEE Transactions on Biomedical Engineering.
[10] Stephen J. Roberts,et al. Markov Models for Automated ECG Interval Analysis , 2003, NIPS.
[11] L. R. Rabiner,et al. A comparative study of several dynamic time-warping algorithms for connected-word recognition , 1981, The Bell System Technical Journal.
[12] Jean-Yves Tourneret,et al. P and twave delineation andwaveform estimation in ECG signals using a block gibbs sampler , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[13] Michael C. Horsch,et al. Dynamic Bayesian networks , 1990 .
[14] Christian Jutten,et al. Twave alternans detection in ecg using Extended Kalman Filter and dualrate EKF , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).
[15] Di Ge,et al. Switching Kalman filter based methods for apnea bradycardia detection from ECG signals. , 2015, Physiological measurement.
[16] Christian Jutten,et al. A Nonlinear Bayesian Filtering Framework for ECG Denoising , 2007, IEEE Transactions on Biomedical Engineering.
[17] W J Tompkins,et al. Applications of artificial neural networks for ECG signal detection and classification. , 1993, Journal of electrocardiology.
[18] Q Li,et al. Dynamic time warping and machine learning for signal quality assessment of pulsatile signals , 2012, Physiological measurement.
[19] C Jutten,et al. Model-based Bayesian filtering of cardiac contaminants from biomedical recordings , 2008, Physiological measurement.
[20] Pablo Laguna,et al. A wavelet-based ECG delineator: evaluation on standard databases , 2004, IEEE Transactions on Biomedical Engineering.
[21] Geoffrey E. Hinton,et al. Variational Learning for Switching State-Space Models , 2000, Neural Computation.
[22] R. Orglmeister,et al. The principles of software QRS detection , 2002, IEEE Engineering in Medicine and Biology Magazine.
[23] Michael J. Black,et al. Modeling and decoding motor cortical activity using a switching Kalman filter , 2004, IEEE Transactions on Biomedical Engineering.
[24] Mohammad Bagher Shamsollahi,et al. ECG Denoising and Compression Using a Modified Extended Kalman Filter Structure , 2008, IEEE Transactions on Biomedical Engineering.
[25] N. S. Lingayat,et al. Detection of P and T-waves in Electrocardiogram , 2008 .
[26] Jérôme Boudy,et al. Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation , 2007, EURASIP J. Adv. Signal Process..
[27] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[28] Mohammad Bagher Shamsollahi,et al. Robust Detection of Premature Ventricular Contractions Using a Wave-Based Bayesian Framework , 2010, IEEE Transactions on Biomedical Engineering.
[29] Patrick E. McSharry,et al. A dynamical model for generating synthetic electrocardiogram signals , 2003, IEEE Transactions on Biomedical Engineering.
[30] Pablo Laguna,et al. A database for evaluation of algorithms for measurement of QT and other waveform intervals in the ECG , 1997, Computers in Cardiology 1997.
[31] Kevin Murphy,et al. Switching Kalman Filters , 1998 .
[32] Christian Jutten,et al. ECG Fiducial Point Extraction Using Switching Kalman Filter , 2018, Comput. Methods Programs Biomed..
[33] Guy Carrault,et al. Improving ECG Beats Delineation With an Evolutionary Optimization Process , 2010, IEEE Transactions on Biomedical Engineering.
[34] Jean-Yves Tourneret,et al. P- and T-Wave Delineation in ECG Signals Using a Bayesian Approach and a Partially Collapsed Gibbs Sampler , 2010, IEEE Transactions on Biomedical Engineering.
[35] J. Espi-Lopez,et al. Application of adaptive signal processing for determining the limits of P and T waves in an ECG , 1998, IEEE Transactions on Biomedical Engineering.
[36] Christian Jutten,et al. ECG segmentation and fiducial point extraction using multi hidden Markov model , 2016, Comput. Biol. Medicine.
[37] Gang Hua,et al. Switching observation models for contour tracking in clutter , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[38] Christian Jutten,et al. Application of Dynamic Time Warping on Kalman Filtering Framework for Abnormal ECG Filtering , 2012, ESANN.
[39] P Caminal,et al. Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database. , 1994, Computers and biomedical research, an international journal.
[40] C. Li,et al. Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.
[41] Christian Jutten,et al. ECG denoising using angular velocity as a state and an observation in an Extended Kalman Filter framework , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.