Application of higher order statistics for atrial arrhythmia classification
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U. Rajendra Acharya | Roshan Joy Martis | Chua Kuang Chua | Jasjit S. Suri | Choo Min Lim | C. M. Lim | Hari Prasad | C. K. Chua | J. Suri | U. Acharya | R. J. Martis | Usha R. Acharya | R. Martis | Hari Prasad | C. Chua
[1] David G. Stork,et al. Pattern Classification , 1973 .
[2] Shantanu Sarkar,et al. A Detector for a Chronic Implantable Atrial Tachyarrhythmia Monitor , 2008, IEEE Transactions on Biomedical Engineering.
[3] G.B. Moody,et al. The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.
[4] D. Levy,et al. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. , 1994, JAMA.
[5] Roshan Joy Martis,et al. ARRHYTHMIA DISEASE DIAGNOSIS USING NEURAL NETWORK, SVM, AND GENETIC ALGORITHM-OPTIMIZED k-MEANS CLUSTERING , 2011 .
[6] B. Logan,et al. Robust detection of atrial fibrillation for a long term telemonitoring system , 2005, Computers in Cardiology, 2005.
[7] José Millet-Roig,et al. How Many Leads Are Necessary for a Reliable Reconstruction of Surface Potentials During Atrial Fibrillation? , 2009, IEEE Transactions on Information Technology in Biomedicine.
[8] Fahim Sufi,et al. Diagnosis of Cardiovascular Abnormalities From Compressed ECG: A Data Mining-Based Approach , 2009, IEEE Transactions on Information Technology in Biomedicine.
[9] U. Rajendra Acharya,et al. Characterization of ECG beats from cardiac arrhythmia using discrete cosine transform in PCA framework , 2013, Knowl. Based Syst..
[10] Chandan Chakraborty,et al. Automated Screening of Arrhythmia Using Wavelet Based Machine Learning Techniques , 2012, Journal of Medical Systems.
[11] D. Levy,et al. Lifetime Risk for Development of Atrial Fibrillation: The Framingham Heart Study , 2004, Circulation.
[12] Yang Wang,et al. A short-time multifractal approach for arrhythmia detection based on fuzzy neural network , 2001, IEEE Transactions on Biomedical Engineering.
[13] Vinod Chandran,et al. Pattern Recognition Using Invariants Defined From Higher Order Spectra- One Dimensional Inputs , 1993, IEEE Trans. Signal Process..
[14] C. M. Lim,et al. Application of higher order statistics/spectra in biomedical signals--a review. , 2010, Medical engineering & physics.
[15] Nikola Bogunovic,et al. Evaluating and comparing performance of feature combinations of heart rate variability measures for cardiac rhythm classification , 2012, Biomed. Signal Process. Control..
[16] Chandan Chakraborty,et al. AUTOMATED DETECTION OF ATRIAL FLUTTER AND FIBRILLATION USING ECG SIGNALS IN WAVELET FRAMEWORK , 2012 .
[17] G. Naccarelli,et al. Increasing prevalence of atrial fibrillation and flutter in the United States. , 2009, The American journal of cardiology.
[18] L. Sornmo,et al. Detection and feature extraction of atrial tachyarrhythmias , 2006, IEEE Engineering in Medicine and Biology Magazine.
[19] Angelo B. Biviano,et al. A new transform for the analysis of complex fractionated atrial electrograms , 2011, Biomedical engineering online.
[20] E. Warman,et al. Management of atrial tachyarrhythmias , 2006, IEEE Engineering in Medicine and Biology Magazine.
[21] Chao Huang,et al. A Novel Method for Detection of the Transition Between Atrial Fibrillation and Sinus Rhythm , 2011, IEEE Transactions on Biomedical Engineering.
[22] Jerry M. Mendel,et al. Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications , 1991, Proc. IEEE.
[23] Chandan Chakraborty,et al. Cardiac decision making using higher order spectra , 2013, Biomed. Signal Process. Control..
[24] R. Hart,et al. Current status of stroke risk stratification in patients with atrial fibrillation. , 2009, Stroke.
[25] U. Rajendra Acharya,et al. ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform , 2013, Biomed. Signal Process. Control..
[26] U. Rajendra Acharya,et al. Automatic Detection of Epileptic EEG Signals Using Higher Order cumulant Features , 2011, Int. J. Neural Syst..
[27] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[28] Edward J Ciaccio,et al. Spectral Profiles of Complex Fractionated Atrial Electrograms Are Different in Longstanding and Acute Onset Atrial Fibrillation Atrial Electrogram Spectra , 2012, Journal of cardiovascular electrophysiology.
[29] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[30] Leif Sörnmo,et al. Frequency tracking of atrial fibrillation using Hidden Markov Models. , 2006, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.
[31] Hasan Garan,et al. A new LMS algorithm for analysis of atrial fibrillation signals , 2012, Biomedical engineering online.
[32] Luca T. Mainardi,et al. Analysis of the dynamics of RR interval series for the detection of atrial fibrillation episodes , 1997, Computers in Cardiology 1997.
[33] Willis J. Tompkins,et al. A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.
[34] Richard P. M. Houben,et al. Analysis of Fractionated Atrial Fibrillation Electrograms by Wavelet Decomposition , 2010, IEEE Transactions on Biomedical Engineering.
[35] Chandan Chakraborty,et al. A two-stage mechanism for registration and classification of ECG using Gaussian mixture model , 2009, Pattern Recognit..
[36] U Rajendra Acharya,et al. Data mining framework for fatty liver disease classification in ultrasound: A hybrid feature extraction paradigm. , 2012, Medical physics.
[37] C. L. Nikias,et al. Signal processing with higher-order spectra , 1993, IEEE Signal Processing Magazine.
[38] G. Tutz,et al. An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. , 2009, Psychological methods.
[39] Stanley Nattel,et al. Chapter 15 – Atrial Tachycardia, Flutter, and Fibrillation , 2005 .
[40] Chandan Chakraborty,et al. Application of Higher Order cumulant Features for Cardiac Health Diagnosis using ECG signals , 2013, Int. J. Neural Syst..
[41] 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.
[42] A. Sahakian,et al. Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity. , 1992, Journal of electrocardiology.
[43] U. Rajendra Acharya,et al. Application of higher order spectra for accurate delineation of atrial arrhythmia , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[44] Ki H. Chon,et al. Atrial Fibrillation Detection Using an iPhone 4S , 2013, IEEE Transactions on Biomedical Engineering.
[45] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[46] Guy Carrault,et al. Atrial activity enhancement by Wiener filtering using an artificial neural network , 2001, IEEE Transactions on Biomedical Engineering.
[47] Leif Sörnmo,et al. Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties , 2001, IEEE Transactions on Biomedical Engineering.
[48] U. Rajendra Acharya,et al. Analysis and Automatic Identification of Sleep Stages Using Higher Order Spectra , 2010, Int. J. Neural Syst..
[49] U. Rajendra Acharya,et al. Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features , 2011, IEEE Transactions on Information Technology in Biomedicine.
[50] Sanjiv M Narayan,et al. Accurate ECG Diagnosis of Atrial Tachyarrhythmias Using Quantitative Analysis: A Prospective Diagnostic and Cost‐Effectiveness Study , 2010, Journal of cardiovascular electrophysiology.
[51] Chandan Chakraborty,et al. Application of principal component analysis to ECG signals for automated diagnosis of cardiac health , 2012, Expert Syst. Appl..