Wavelet Entropy Automatically Detects Episodes of Atrial Fibrillation from Single-Lead Electrocardiograms
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Raúl Alcaraz | José Joaquín Rieta | Manuel García | Juan Ródenas | J. J. Rieta | J. Ródenas | R. Alcaraz | Manuel García | J. Rieta
[1] V. Frolkis,et al. Aging of the Brain , 1982 .
[2] M. Ezekowitz,et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. , 2014, Circulation.
[3] Haran Burri,et al. Usefulness of P‐Wave Signal Averaging to Predict Atrial Fibrillation Recurrences after Electrical Cardioversion , 2014, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.
[4] P. Laguna,et al. Signal Processing , 2002, Yearbook of Medical Informatics.
[5] C. Israel,et al. Long-term risk of recurrent atrial fibrillation as documented by an implantable monitoring device: implications for optimal patient care. , 2004, Journal of the American College of Cardiology.
[6] Kenneth A Ellenbogen,et al. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (updating the 2006 guideline): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. , 2011, Circulation.
[7] J. R. Moorman,et al. Accurate estimation of entropy in very short physiological time series: the problem of atrial fibrillation detection in implanted ventricular devices. , 2011, American journal of physiology. Heart and circulatory physiology.
[8] S. Mallat. A wavelet tour of signal processing , 1998 .
[9] Raúl Alcaraz,et al. Application of the phasor transform for automatic delineation of single-lead ECG fiducial points , 2010, Physiological measurement.
[10] M. Harris,et al. Model-Based Atrial Fibrillation Detection , 2012 .
[11] Silvia G Priori,et al. 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. , 2011, Circulation.
[12] Shuming Ye,et al. High accuracy in automatic detection of atrial fibrillation for Holter monitoring , 2012, Journal of Zhejiang University SCIENCE B.
[13] P. Platonov,et al. Noninvasive Evidence of Shortened Atrial Refractoriness during Sinus Rhythm in Patients with Paroxysmal Atrial Fibrillation , 2009, Pacing and clinical electrophysiology : PACE.
[14] N. Rao,et al. A Novel Method for Real‐Time Atrial Fibrillation Detection in Electrocardiograms Using Multiple Parameters , 2014, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.
[15] Haran Burri,et al. Value of P-wave signal averaging to predict atrial fibrillation recurrences after pulmonary vein isolation. , 2013, 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.
[16] Behnaz Ghoraani,et al. Rate-independent detection of atrial fibrillation by statistical modeling of atrial activity , 2015, Biomed. Signal Process. Control..
[17] S. Lévy,et al. Atrial fibrillation: current knowledge and recommendations for management. Working Group on Arrhythmias of the European Society of Cardiology. , 1998, European heart journal.
[18] Henggui Zhang,et al. A multi-step method with signal quality assessment and fine-tuning procedure to locate maternal and fetal QRS complexes from abdominal ECG recordings , 2014, Physiological measurement.
[19] Raúl Alcaraz,et al. Application of Wavelet Entropy to Predict Atrial Fibrillation Progression from the Surface ECG , 2012, Comput. Math. Methods Medicine.
[20] E. Basar,et al. Wavelet entropy: a new tool for analysis of short duration brain electrical signals , 2001, Journal of Neuroscience Methods.
[21] Magda Tsolaki,et al. Functional disorganization of small-world brain networks in mild Alzheimer's Disease and amnestic Mild Cognitive Impairment: an EEG study using Relative Wavelet Entropy (RWE) , 2014, Front. Aging Neurosci..
[22] Qingyun Du,et al. Application of Entropy-Based Attribute Reduction and an Artificial Neural Network in Medicine: A Case Study of Estimating Medical Care Costs Associated with Myocardial Infarction , 2014, Entropy.
[23] Raymond C S Seet,et al. Prolonged Rhythm Monitoring for the Detection of Occult Paroxysmal Atrial Fibrillation in Ischemic Stroke of Unknown Cause , 2011, Circulation.
[24] I Dotsinsky,et al. Optimization of bi-directional digital filtering for drift suppression in electrocardiogram signals , 2004, Journal of medical engineering & technology.
[25] E. Helfenbein,et al. Improvements in atrial fibrillation detection for real-time monitoring. , 2009, Journal of electrocardiology.
[26] H. Umar. Clinical decision-making using computers: opportunities and limitations. , 2002, Dental clinics of North America.
[27] D. Drachman. Aging of the brain, entropy, and Alzheimer disease , 2006, Neurology.
[28] Haitham M. Al-Angari,et al. Atrial fibrillation and waveform characterization. A time domain perspective in the surface ECG. , 2006, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[29] G. Bortolan,et al. Automatic detection of atrial fibrillation and flutter by wave rectification method. , 2001, Journal of medical engineering & technology.
[30] Paul S Addison,et al. Wavelet transforms and the ECG: a review , 2005, Physiological measurement.
[31] Chao Huang,et al. A Novel Method for Detection of the Transition Between Atrial Fibrillation and Sinus Rhythm , 2011, IEEE Transactions on Biomedical Engineering.
[32] F. Acar Savaci,et al. Continuous time wavelet entropy of auditory evoked potentials , 2010, Comput. Biol. Medicine.
[33] Marco Proietti,et al. Asymptomatic versus symptomatic atrial fibrillation: A systematic review of age/gender differences and cardiovascular outcomes. , 2015, International journal of cardiology.
[34] Pablo Laguna,et al. Bioelectrical Signal Processing in Cardiac and Neurological Applications , 2005 .
[35] Ki H. Chon,et al. Time-Varying Coherence Function for Atrial Fibrillation Detection , 2013, IEEE Transactions on Biomedical Engineering.
[36] Giovanni Calcagnini,et al. Time‐Domain and Morphological Analysis of the P‐Wave. Part I: Technical Aspects for Automatic Quantification of P‐Wave Features , 2008, Pacing and clinical electrophysiology : PACE.
[37] G. Hindricks,et al. P-wave evidence as a method for improving algorithm to detect atrial fibrillation in insertable cardiac monitors. , 2014, Heart rhythm.
[38] M. Aguilar,et al. Meta-analysis: Antithrombotic Therapy to Prevent Stroke in Patients Who Have Nonvalvular Atrial Fibrillation , 2007, Annals of Internal Medicine.
[39] Witold Pedrycz,et al. ECG signal processing, classification, and interpretation : , 2012 .
[40] Xiao Hu,et al. Improved wavelet entropy calculation with window functions and its preliminary application to study intracranial pressure , 2013, Comput. Biol. Medicine.
[41] J. Rafiee,et al. Wavelet basis functions in biomedical signal processing , 2011, Expert Syst. Appl..
[42] Emma Pickwell-MacPherson,et al. Automatic online detection of atrial fibrillation based on symbolic dynamics and Shannon entropy , 2014, BioMedical Engineering OnLine.
[43] Youhua Zhang,et al. Ventricular Rate Control During Atrial Fibrillation and AV Node Modifications: , 2004, Pacing and clinical electrophysiology : PACE.
[44] Sheng Lu,et al. Automatic Real Time Detection of Atrial Fibrillation , 2009, Annals of Biomedical Engineering.
[45] Kayvan Najarian,et al. Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey , 2013, TheScientificWorldJournal.
[46] Haitham M. Al-Angari,et al. Atrial fibrillation and waveform characterization , 2006, IEEE Engineering in Medicine and Biology Magazine.
[47] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[48] P. Kirchhof,et al. What are the costs of 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.
[49] Vaidotas Marozas,et al. Detection of occult paroxysmal atrial fibrillation , 2014, Medical & Biological Engineering & Computing.
[50] Alireza Mehrnia,et al. Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine , 2015, Comput. Biol. Medicine.
[51] M. Ezekowitz,et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. , 2014, Circulation.
[52] L Glass,et al. Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and ΔRR intervals , 2001, Medical and Biological Engineering and Computing.
[53] D. Gladstone,et al. Screening for undiagnosed atrial fibrillation in the community , 2014, Current opinion in cardiology.
[54] A. Sahakian,et al. Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity. , 1992, Journal of electrocardiology.
[55] S Swiryn,et al. Automated discrimination between atrial fibrillation and atrial flutter in the resting 12-lead electrocardiogram. , 2000, Journal of electrocardiology.
[56] I. Romero,et al. Comparative study of algorithms for Atrial Fibrillation detection , 2011, 2011 Computing in Cardiology.
[57] Sylvain Arlot,et al. A survey of cross-validation procedures for model selection , 2009, 0907.4728.
[58] Ki H. Chon,et al. Atrial Fibrillation Detection Using an iPhone 4S , 2013, IEEE Transactions on Biomedical Engineering.
[59] S. Saksena,et al. Relationship between atrial tachyarrhythmias and symptoms. , 2005, Heart rhythm.
[60] Stanley Nattel,et al. Management of atrial fibrillation in the year 2033: new concepts, tools, and applications leading to personalized medicine. , 2013, The Canadian journal of cardiology.
[61] Raúl Alcaraz,et al. A review on sample entropy applications for the non-invasive analysis of atrial fibrillation electrocardiograms , 2010, Biomed. Signal Process. Control..
[62] Andreas Voss,et al. Analyses of Heart Rate, Respiration and Cardiorespiratory Coupling in Patients with Schizophrenia , 2015, Entropy.