Nonlinear stochastic modeling and analysis of cardiovascular system dynamics - Diagnostic and prognostic applications
暂无分享,去创建一个
[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.