Electrocardiogram modeling during paroxysmal atrial fibrillation: application to the detection of brief episodes
暂无分享,去创建一个
Vaidotas Marozas | Julien Oster | Leif Sörnmo | Andrius Petrenas | Jurgita Skibarkiene | Raimondas Kubilius | Andrius Sološenko | L. Sörnmo | A. Petrėnas | Andrius Sološenko | V. Marozas | J. Oster | R. Kubilius | J. Skibarkiene
[1] R. Virmani,et al. Embolic Myocardial Infarction as a Consequence of Atrial Fibrillation: A Prevailing Disease of the Future. , 2015, Circulation.
[2] Witold Pedrycz,et al. ECG signal processing, classification, and interpretation : , 2012 .
[3] J. Millet,et al. Noninvasive Localization of Maximal Frequency Sites of Atrial Fibrillation by Body Surface Potential Mapping , 2013, Circulation. Arrhythmia and electrophysiology.
[4] S. Mittal,et al. Correlation of QT interval correction methods during atrial fibrillation and sinus rhythm. , 2013, The American journal of cardiology.
[5] Julien Oster,et al. An artificial model of the electrocardiogram during paroxysmal atrial fibrillation , 2013, Computing in Cardiology 2013.
[6] H. Bazett,et al. AN ANALYSIS OF THE TIME‐RELATIONS OF ELECTROCARDIOGRAMS. , 1997 .
[7] Valentina D. A. Corino,et al. Atrioventricular nodal function during atrial fibrillation: Model building and robust estimation , 2013, Biomed. Signal Process. Control..
[8] Leif Sörnmo,et al. Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation , 2001, IEEE Transactions on Biomedical Engineering.
[9] P. Laguna,et al. Adaptive estimation of QRS complex wave features of ECG signal by the hermite model , 2007, Medical and Biological Engineering and Computing.
[10] Ying Sun,et al. Gaussian pulse decomposition: An intuitive model of electrocardiogram waveforms , 1997, Annals of Biomedical Engineering.
[11] K. Kelly,et al. Atrial fibrillation detected by mobile cardiac outpatient telemetry in cryptogenic TIA or stroke , 2008, Neurology.
[12] S. Connolly,et al. Progression to chronic atrial fibrillation after the initial diagnosis of paroxysmal atrial fibrillation: results from the Canadian Registry of Atrial Fibrillation. , 2005, American Heart Journal.
[13] Chao Huang,et al. A Novel Method for Detection of the Transition Between Atrial Fibrillation and Sinus Rhythm , 2011, IEEE Transactions on Biomedical Engineering.
[14] Ye Li,et al. Atrial activity extraction from single lead ECG recordings: Evaluation of two novel methods , 2013, Comput. Biol. Medicine.
[15] Sebastian Zaunseder,et al. An ECG simulator for generating maternal-foetal activity mixtures on abdominal ECG recordings , 2014, Physiological measurement.
[16] A. Go,et al. Detection of Paroxysmal Atrial Fibrillation by 30-Day Event Monitoring in Cryptogenic Ischemic Stroke: The Stroke and Monitoring for PAF in Real Time (SMART) Registry , 2012, Stroke.
[17] Ki H. Chon,et al. Time-Varying Coherence Function for Atrial Fibrillation Detection , 2013, IEEE Transactions on Biomedical Engineering.
[18] Valentina D. A. Corino,et al. An Atrioventricular Node Model for Analysis of the Ventricular Response During Atrial Fibrillation , 2011, IEEE Transactions on Biomedical Engineering.
[19] Olle Pahlm,et al. A Method for Evaluation of QRS Shape Features Using a Mathematical Model for the ECG , 1981, IEEE Transactions on Biomedical Engineering.
[20] Steven M Bradley,et al. Early detection of occult atrial fibrillation and stroke prevention , 2015, Heart.
[21] Patrick E. McSharry,et al. A dynamical model for generating synthetic electrocardiogram signals , 2003, IEEE Transactions on Biomedical Engineering.
[22] Kennedy R. Lees,et al. Detection of Atrial Fibrillation After Ischemic Stroke or Transient Ischemic Attack: A Systematic Review and Meta-Analysis , 2014, Stroke.
[23] MARCELLO DISERTORI,et al. Deterioration of Organization in the First Minutes of Atrial Fibrillation: A Beat‐to‐Beat Analysis of Cycle Length and Wave Similarity , 2007, Journal of cardiovascular electrophysiology.
[24] Raymond C S Seet,et al. Paroxysmal atrial fibrillation in cryptogenic stroke: a case-control study. , 2013, Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association.
[25] Michael T. Mullen,et al. Predictors of Finding Occult Atrial Fibrillation After Cryptogenic Stroke , 2015, Stroke.
[26] Steven Swiryn,et al. Abrupt changes in fibrillatory wave characteristics at the termination of paroxysmal atrial fibrillation in humans. , 2007, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.
[27] Raúl Alcaraz,et al. Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation , 2009, Comput. Methods Programs Biomed..
[28] Vaidotas Marozas,et al. An Echo State Neural Network for QRST Cancellation During Atrial Fibrillation , 2012, IEEE Transactions on Biomedical Engineering.
[29] A. Mahajan,et al. The Evolution and Application of Cardiac Monitoring for Occult Atrial Fibrillation in Cryptogenic Stroke and TIA , 2016, Current Treatment Options in Neurology.
[30] 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.
[31] Vijayshree Yadav,et al. Use of Cannabinoids for Spasticity and Pain Management in MS , 2015, Current Treatment Options in Neurology.
[32] G. Lip,et al. Stroke prevention in atrial fibrillation , 2016, The Lancet.
[33] Jelena Kovacevic,et al. Efficient Compression of QRS Complexes Using Hermite Expansion , 2012, IEEE Transactions on Signal Processing.
[34] Giovanni Calcagnini,et al. P-Wave Morphology Assessment by a Gaussian Functions-Based Model in Atrial Fibrillation Patients , 2007, IEEE Transactions on Biomedical Engineering.
[35] Emma Pickwell-MacPherson,et al. Automatic online detection of atrial fibrillation based on symbolic dynamics and Shannon entropy , 2014, BioMedical Engineering OnLine.
[36] Roberto Sassi,et al. Analysis of Surface Atrial Signals: Time Series with Missing Data? , 2009, Annals of Biomedical Engineering.
[37] Jan Gierałtowski,et al. Modeling heart rate variability including the effect of sleep stages. , 2016, Chaos.
[38] Mattias Ohlsson,et al. Detecting acute myocardial infarction in the 12-lead ECG using Hermite expansions and neural networks , 2004, Artif. Intell. Medicine.
[39] M. Harris,et al. Model-Based Atrial Fibrillation Detection , 2012 .
[40] Pablo Laguna,et al. Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves , 2017, IEEE Transactions on Biomedical Engineering.
[41] Panos Vardas,et al. Prognosis and treatment of atrial fibrillation patients by European cardiologists: one year follow-up of the EURObservational Research Programme-Atrial Fibrillation General Registry Pilot Phase (EORP-AF Pilot registry). , 2014, European heart journal.
[42] G. Dower,et al. On Deriving the Electrocardiogram from Vectorcardiographic Leads , 1980, Clinical cardiology.
[43] Ralf Bousseljot,et al. Nutzung der EKG-Signaldatenbank CARDIODAT der PTB über das Internet , 2009 .
[44] Vaidotas Marozas,et al. A Noise-Adaptive Method for Detection of Brief Episodes of Paroxysmal Atrial Fibrillation , 2013, Computing in Cardiology 2013.
[45] Vaidotas Marozas,et al. Detection of occult paroxysmal atrial fibrillation , 2014, Medical & Biological Engineering & Computing.
[46] Behnaz Ghoraani,et al. Rate-independent detection of atrial fibrillation by statistical modeling of atrial activity , 2015, Biomed. Signal Process. Control..
[47] Steve Enger,et al. Abnormal atrial activation in young patients with lone atrial fibrillation. , 2011, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.
[48] Steven Swiryn,et al. Derivation of orthogonal leads from the 12-lead electrocardiogram. Performance of an atrial-based transform for the derivation of P loops. , 2008, Journal of electrocardiology.
[49] Travis J. Moss,et al. Heart rate dynamics distinguish among atrial fibrillation, normal sinus rhythm and sinus rhythm with frequent ectopy , 2015, Physiological measurement.
[50] S. Connolly,et al. Progression to chronic atrial fibrillation after the initial diagnosis of paroxysmal atrial fibrillation: results from the Canadian Registry of Atrial Fibrillation. , 2005, American heart journal.
[51] Raúl Alcaraz,et al. Surface ECG organization analysis to predict paroxysmal atrial fibrillation termination , 2009, Comput. Biol. Medicine.
[52] J M Rawles,et al. The QT interval in atrial fibrillation. , 1989, British heart journal.
[53] David J. Gladstone,et al. Atrial Premature Beats Predict Atrial Fibrillation in Cryptogenic Stroke: Results From the EMBRACE Trial , 2015, Stroke.
[54] Christian Jutten,et al. Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals , 2007, EURASIP J. Adv. Signal Process..
[55] A. Rabinstein,et al. Atrial fibrillation detected by mobile cardiac outpatient telemetry in cryptogenic TIA or stroke , 2009 .
[56] Sheng Lu,et al. Automatic Real Time Detection of Atrial Fibrillation , 2009, Annals of Biomedical Engineering.
[57] James McNames,et al. Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes , 2004, IEEE Transactions on Biomedical Engineering.
[58] P. Andersen,et al. New‐Onset Atrial Fibrillation is Associated With Cardiovascular Events Leading to Death in a First Time Myocardial Infarction Population of 89 703 Patients With Long‐Term Follow‐Up: A Nationwide Study , 2014, Journal of the American Heart Association.
[59] Vaidotas Marozas,et al. Low-complexity detection of atrial fibrillation in continuous long-term monitoring , 2015, Comput. Biol. Medicine.
[60] Leif Sörnmo,et al. Sequential characterization of atrial tachyarrhythmias based on ECG time-frequency analysis , 2004, IEEE Transactions on Biomedical Engineering.
[61] M. Masè,et al. Dynamics of AV coupling during human atrial fibrillation: role of atrial rate. , 2015, American journal of physiology. Heart and circulatory physiology.
[62] Faisal Rahman,et al. Global epidemiology of atrial fibrillation , 2014, Nature Reviews Cardiology.
[63] Alberto Herreros,et al. Age-related changes in P wave morphology in healthy subjects , 2007, BMC cardiovascular disorders.
[64] M. Allessie,et al. Atrial fibrillation begets atrial fibrillation. A study in awake chronically instrumented goats. , 1995, Circulation.
[65] E. Helfenbein,et al. Improvements in atrial fibrillation detection for real-time monitoring. , 2009, Journal of electrocardiology.
[66] S. Osowski,et al. On-line heart beat recognition using hermite polynomials and neuro-fuzzy network , 2002, IMTC/2002. Proceedings of the 19th IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.00CH37276).
[67] Leif Sörnmo,et al. Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties , 2001, IEEE Transactions on Biomedical Engineering.
[68] P. Platonov,et al. Electrocardiographic and Echocardiographic predictors of paroxysmal atrial fibrillation detected after ischemic stroke , 2016, BMC Cardiovascular Disorders.