Nonlinear stochastic modeling and analysis of cardiovascular system dynamics - Diagnostic and prognostic applications

[1]  W.J. Tompkins,et al.  Neural-network-based adaptive matched filtering for QRS detection , 1992, IEEE Transactions on Biomedical Engineering.

[2]  G. Burch,et al.  Studies of the Spatial Vectorcardiogram in Normal Man , 1953, Circulation.

[3]  J. Morgan,et al.  Problems in the Analysis of Survey Data, and a Proposal , 1963 .

[4]  Leif Sörnmo,et al.  Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation , 2001, IEEE Transactions on Biomedical Engineering.

[5]  Alan V. Sahakian,et al.  The influence of QRS cancellation on signal characteristics of atrial fibrillation in the surface electrocardiogram , 2002, Computers in Cardiology.

[6]  Alan V. Sahakian,et al.  Vector analysis of atrial activity from surface ECGs recorded during atrial fibrillation , 2002, Computers in Cardiology.

[7]  E. Lorenz Atmospheric Predictability as Revealed by Naturally Occurring Analogues , 1969 .

[8]  S. Swiryn,et al.  Analysis of the surface electrocardiogram to predict termination of atrial fibrillation: the 2004 computers in cardiology/physionet challenge , 2004, Computers in Cardiology, 2004.

[9]  Vincent Jacquemet,et al.  Vectorcardiographic lead systems for the characterization of atrial fibrillation. , 2007, Journal of electrocardiology.

[10]  F. Takens Detecting strange attractors in turbulence , 1981 .

[11]  H. Kantz,et al.  Recurrence plot analysis of nonstationary data: the understanding of curved patterns. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  H E Stanley,et al.  Statistical physics and physiology: monofractal and multifractal approaches. , 1999, Physica A.

[13]  Kevin Judd,et al.  Modeling continuous processes from data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Jan A. Kors,et al.  The Electrical T-Axis and the Spatial QRS-T Angle Are Independent Predictors of Long-Term Mortality in Patients Admitted with Acute Ischemic Chest Pain , 2004, Cardiology.

[15]  Noboru Okamoto,et al.  Diagnostic accuracy of the vectorcardiogram and electrocardiogram: A cooperative study , 1966 .

[16]  L. Sornmo,et al.  Predicting spontaneous termination of atrial fibrillation with time-frequency information , 2004, Computers in Cardiology, 2004.

[17]  A. Cohen,et al.  Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples , 1965 .

[18]  D. Ruelle,et al.  Recurrence Plots of Dynamical Systems , 1987 .

[19]  R. A. Helm,et al.  Simple Quantitative Vectorcardiographic Criteria for the Diagnosis of Right Ventricular Hypertrophy , 1973, Circulation.

[20]  H. Kantz,et al.  Nonlinear time series analysis , 1997 .

[21]  R Hegger,et al.  Denoising human speech signals using chaoslike features. , 2000, Physical review letters.

[22]  R. Komanduri,et al.  Nonlinear adaptive wavelet analysis of electrocardiogram signals. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Lakhtakia,et al.  Analysis of sensor signals shows turning on a lathe exhibits low-dimensional chaos. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[24]  G. Boudreaux-Bartels,et al.  Wavelet transform-based QRS complex detector , 1999, IEEE Transactions on Biomedical Engineering.

[25]  D. Hayn,et al.  Automated prediction of spontaneous termination of atrial fibrillation from electrocardiograms , 2004, Computers in Cardiology, 2004.

[26]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[27]  G. Dower,et al.  On Deriving the Electrocardiogram from Vectorcardiographic Leads , 1980, Clinical cardiology.

[28]  H. Abarbanel,et al.  Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[29]  H. Helenius,et al.  Automated ECG injury scores in the prediction of the myocardial infarction (AMI) size , 1998, Computers in Cardiology 1998. Vol. 25 (Cat. No.98CH36292).

[30]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[31]  Steven Swiryn,et al.  Surface ECG vector characteristics of organized and disorganized atrial activity during atrial fibrillation. , 2004, Journal of electrocardiology.

[32]  M. Varanini,et al.  Predicting the end of an atrial fibrillation episode: the physionet challenge , 2004, Computers in Cardiology, 2004.

[33]  M. Casdagli Recurrence plots revisited , 1997 .

[34]  Y. Tseng,et al.  Maximal spatial ST-vector patterns in patients with acute anteroseptal myocardial infarction. , 1994, International journal of cardiology.

[35]  Martin Stridh,et al.  Frequency trends of atrial fibrillation using the surface ECG , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[36]  G. Moody,et al.  Spontaneous termination of atrial fibrillation: a challenge from physionet and computers in cardiology 2004 , 2004, Computers in Cardiology, 2004.

[37]  Wolfgang Kinzel,et al.  Learning and predicting time series by neural networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  A. Wallace,et al.  Characteristics of the normal vectorcardiogram recorded with the Frank lead system. , 1962, The American journal of cardiology.

[39]  H. Kantz,et al.  Optimizing of recurrence plots for noise reduction. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  H V Pipberger ADVANTAGES OF THREE LEAD CARDIOGRAPHIC RECORDINGS * , 1965, Annals of the New York Academy of Sciences.

[41]  Soundar R. T. Kumara,et al.  The neighborhood method and its coupling with the wavelet method for signal separation of chaotic signals , 2002, Signal Process..

[42]  J. Zbilut,et al.  Recurrence quantification in epileptic EEGs , 2001 .

[43]  Aslak Tveito,et al.  Computing the size and location of myocardial ischemia using measurements of ST-segment shift , 2006, IEEE Transactions on Biomedical Engineering.

[44]  Adaptive recurrent filter for ectopic beat and arrhythmia detection , 1988, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[45]  Leif Sörnmo,et al.  Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties , 2001, IEEE Transactions on Biomedical Engineering.

[46]  J. Kurths,et al.  Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[47]  Renzo Antolini,et al.  Complex dynamics underlying the human electrocardiogram , 1992, Biological Cybernetics.

[48]  Bonpei Takase,et al.  11) INCIDENCES OF CORONARY ARTERY STENOSIS AND MEAN QRS VECTOR ON THE FRONTAL PLANE VECTORCARDIOGRAM IN PATIENTS WITH INFERIOR MYOCARDIAL INFARCTION , 1983 .

[49]  L. Sornmo,et al.  Spatiotemporal QRST cancellation techniques for improved characterization of atrial fibrillation in the surface ECG , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[50]  Daniel Lemire,et al.  Wavelet time entropy, T wave morphology and myocardial ischemia , 2000, IEEE Transactions on Biomedical Engineering.

[51]  A. Walden,et al.  Wavelet Methods for Time Series Analysis , 2000 .

[52]  Alessandro Giuliani,et al.  Recurrence quantification analysis as an empirical test to distinguish relatively short deterministic versus random number series , 2000 .

[53]  M. Mlynash,et al.  Automated QRST subtraction algorithm for analysis of T wave obscured ectopic atrial beats , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[54]  Paul S Addison,et al.  Wavelet transforms and the ECG: a review , 2005, Physiological measurement.

[55]  D. Dubin Rapid Interpretation of EKG's , 1977 .

[56]  C. Sanchez,et al.  Packet wavelet decomposition: An approach for atrial activity extraction , 2002, Computers in Cardiology.

[57]  Robert Plonsey,et al.  Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .

[58]  Fraser,et al.  Independent coordinates for strange attractors from mutual information. , 1986, Physical review. A, General physics.

[59]  G E Dower,et al.  Deriving the 12-lead electrocardiogram from four (EASI) electrodes. , 1988, Journal of electrocardiology.

[60]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[61]  K. Talwar,et al.  Spatial vectorcardiogram in acute inferior wall myocardial infarction: its utility in identification of patients prone to complete heart block. , 1989, International journal of cardiology.

[62]  Jeffrey M. Hausdorff,et al.  Fractal dynamics in physiology: Alterations with disease and aging , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[63]  Akhlesh Lakhtakia,et al.  Dependence of computed trajectory on step-size in a nonlinear dynamic system: an investigation into cutting tool dynamics , 1995 .

[64]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.

[65]  Katerina Hnatkova,et al.  Optimal lead configuration in the detection and subtraction of QRS and T wave templates in atrial fibrillation , 1998, Computers in Cardiology 1998. Vol. 25 (Cat. No.98CH36292).

[66]  L. Amaral,et al.  Multifractality in human heartbeat dynamics , 1998, Nature.

[67]  J.J. Rieta,et al.  Estimation of atrial fibrillatory waves from one-lead ECGs using principal component analysis concepts , 2004, Computers in Cardiology, 2004.

[68]  Pablo Laguna,et al.  QRS Slopes for Detection and Characterization of Myocardial Ischemia , 2008, IEEE Transactions on Biomedical Engineering.

[69]  G. Furgi,et al.  Quantification of Poincare' maps for the evaluation of heart rate variability , 1994, Computers in Cardiology 1994.

[70]  Patrick E. McSharry,et al.  A dynamical model for generating synthetic electrocardiogram signals , 2003, IEEE Transactions on Biomedical Engineering.

[71]  O. Pahlm,et al.  Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. , 1988, Journal of electrocardiology.

[72]  Steven Swiryn,et al.  Atrial Fibrillatory Wave Characteristics on Surface Electrogram: , 2004, Journal of cardiovascular electrophysiology.

[73]  M. Lemay,et al.  Computers in cardiology/physionet challenge 2004: AF classification based on clinical features , 2004, Computers in Cardiology, 2004.

[74]  H. Koch,et al.  The PhysioNet/Computers in Cardiology Challenge 2006: QT interval measurement , 2006, 2006 Computers in Cardiology.

[76]  Steven Swiryn,et al.  Atrial flutter vector loops derived from the surface ECG: does the plane of the loop correspond anatomically to the macroreentrant circuit? , 2003, Journal of electrocardiology.

[77]  A Benchimol,et al.  Comparison of the electrocardiogram and vectorcardiogram for the diagnosis of left atrial enlargement. , 1976, Journal of electrocardiology.

[78]  Willis J. Tompkins,et al.  Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database , 1986, IEEE Transactions on Biomedical Engineering.

[79]  José Carlos Teixeira de Barros Moraes,et al.  A QRS complex detection algorithm using electrocardiogram leads , 2002, Computers in Cardiology.

[80]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

[81]  Yuanyuan Wang,et al.  Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot. , 2008, Medical engineering & physics.

[82]  V Kumar,et al.  QRS detection using new wavelets , 2002, Journal of medical engineering & technology.

[83]  A. Witham Quantitation of the vectorcardiogram. , 1966, American heart journal.

[84]  Jarmo Hietarinta,et al.  Stochastic model for heart-rate fluctuations. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[85]  J. L. Willems,et al.  Comparison of the classification ability of the electrocardiogram and vectorcardiogram. , 1987, The American journal of cardiology.

[86]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[87]  Satish T. S. Bukkapatnam,et al.  Local eigenfunctions based suboptimal wavelet packet representation of contaminated chaotic signals , 1999 .

[88]  Truong Q. Nguyen,et al.  Wavelets and filter banks , 1996 .

[89]  R. Lewis An Introduction to Classification and Regression Tree (CART) Analysis , 2000 .

[90]  R. Orglmeister,et al.  The principles of software QRS detection , 2002, IEEE Engineering in Medicine and Biology Magazine.

[91]  David S. Stoffer,et al.  Time series analysis and its applications , 2000 .

[92]  José Millet-Roig,et al.  Atrial activity extraction from atrial fibrillation episodes based on maximum likelihood source separation , 2005, Signal Process..

[93]  Richard J. Povinelli,et al.  Rhythm classification using reconstructed phase space of signal frequency sub-bands , 2003, Computers in Cardiology, 2003.

[94]  Aneta Stefanovska,et al.  Physics of the human cardiovascular system , 1999 .

[95]  Paul J. Wang,et al.  Spatial QRS-T angle predicts cardiac death in a clinical population. , 2005, Heart rhythm.

[96]  Philip Langley,et al.  Surface Atrial Frequency Analysis in Patients with Atrial Fibrillation: , 2004, Journal of cardiovascular electrophysiology.

[97]  J. Millet-Roig,et al.  Atrial activity extraction based on blind source separation as an alternative to QRST cancellation for atrial fibrillation analysis , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[98]  Alan V. Sahakian,et al.  Stationarity of surface ECG atrial fibrillatory wave characteristics in the time and frequency domains in clinically stable patients , 2003, Computers in Cardiology, 2003.

[99]  Kristina M. Ropella,et al.  Correspondence between the frequency domain characteristics of simultaneous surface and intra-atrial recordings of atrial fibrillation , 1994, Computers in Cardiology 1994.

[100]  Ivaylo I Christov,et al.  Real time electrocardiogram QRS detection using combined adaptive threshold , 2004, Biomedical engineering online.

[101]  P. Langley,et al.  Frequency analysis of atrial fibrillation , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[102]  G E Dower,et al.  XYZ data interpreted by a 12-lead computer program using the derived electrocardiogram. , 1979, Journal of electrocardiology.

[103]  Lennart Bergfeldt,et al.  T vector and loop characteristics in coronary artery disease and during acute ischemia. , 2004, Heart rhythm.

[104]  M. Risk,et al.  Measurement of QT interval and duration of the QRS complex at different ECG sampling rates , 2005, Computers in Cardiology, 2005.

[105]  Giovanni Bortolan,et al.  Myocardial infarction and ischemia characterization from T-loop morphology in VCG , 2001, Computers in Cardiology 2001. Vol.28 (Cat. No.01CH37287).

[106]  Martin T. Hagan,et al.  Neural network design , 1995 .

[107]  A. Taddei,et al.  Long-term ST database: A reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia , 2003, Medical and Biological Engineering and Computing.

[108]  L. A. Aguirre,et al.  Piecewise affine models of chaotic attractors: the Rossler and Lorenz systems. , 2006, Chaos.

[109]  Dale Dubin,et al.  Rapid interpretation of EKG's : an interactive course , 2000 .

[110]  Stefan P Nelwan,et al.  Reconstruction of the 12-lead electrocardiogram from reduced lead sets. , 2004, Journal of electrocardiology.

[111]  S. Barold Willem Einthoven and the birth of clinical electrocardiography a hundred years ago. , 2003, Cardiac electrophysiology review.

[112]  Hui Yang,et al.  Classification of atrial fibrillation episodes from sparse electrocardiogram data. , 2008, Journal of electrocardiology.