Intelligent Diagnosis of Cardiovascular Diseases Utilizing ECG Signals
暂无分享,去创建一个
Yangsheng Xu | Jia Liu | Yan Lu | Xinyu Wu | Jingyu Yan
[1] Sadik Kara,et al. Atrial fibrillation classification with artificial neural networks , 2007, Pattern Recognit..
[2] Amjed S. Al-Fahoum,et al. A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques , 2005, IEEE Transactions on Biomedical Engineering.
[3] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[5] Manuel Blanco-Velasco,et al. ECG signal denoising and baseline wander correction based on the empirical mode decomposition , 2008, Comput. Biol. Medicine.
[6] Larry D. Hostetler,et al. The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.
[7] C. Li,et al. Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.
[8] A. Murray,et al. Comparison of four techniques for recognition of ventricular fibrillation from the surface ECG , 1993, Medical and Biological Engineering and Computing.
[9] Stanislaw Osowski,et al. ECG beat recognition using fuzzy hybrid neural network , 2001, IEEE Trans. Biomed. Eng..
[10] Keinosuke Fukunaga,et al. Introduction to statistical pattern recognition (2nd ed.) , 1990 .
[11] Jia Liu,et al. Model-based feature extraction of electrocardiogram using mean shift , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[13] Metin Akay,et al. Wiley encyclopedia of biomedical engineering , 2006 .
[14] C.D. Nugent,et al. Supervised classification models to detect the presence of old myocardial infarction in Body Surface Potential Maps , 2006, 2006 Computers in Cardiology.
[15] D. Kreiseler,et al. Automatisierte EKG-Auswertung mit Hilfe der EKG-Signaldatenbank CARDIODAT der PTB , 1995 .
[16] Christian Jutten,et al. A Nonlinear Bayesian Filtering Framework for ECG Denoising , 2007, IEEE Transactions on Biomedical Engineering.
[17] G. Baudat,et al. Generalized Discriminant Analysis Using a Kernel Approach , 2000, Neural Computation.
[18] Christopher J. C. Burges,et al. A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.
[19] Han-Pang Huang,et al. Recognition of Electromyographic Signals Using Cascaded Kernel Learning Machine , 2007, IEEE/ASME Transactions on Mechatronics.
[20] Ralf Bousseljot,et al. Nutzung der EKG-Signaldatenbank CARDIODAT der PTB über das Internet , 2009 .
[21] Chunru Wan,et al. Classification using support vector machines with graded resolution , 2005, 2005 IEEE International Conference on Granular Computing.
[22] Seyed Kamaledin Setarehdan,et al. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal , 2008, Artif. Intell. Medicine.
[23] Patrick E. McSharry,et al. A dynamical model for generating synthetic electrocardiogram signals , 2003, IEEE Transactions on Biomedical Engineering.
[24] Kap Luk Chan,et al. Classification of electrocardiogram using hidden Markov models , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).
[25] Carsten Peterson,et al. Clustering ECG complexes using Hermite functions and self-organizing maps , 2000, IEEE Trans. Biomed. Eng..
[26] D.I. Fotiadis,et al. A method for arrhythmic episode classification in ECGs using fuzzy logic and Markov models , 2004, Computers in Cardiology, 2004.
[27] Samjin Choi. Detection of valvular heart disorders using wavelet packet decomposition and support vector machine , 2008, Expert Syst. Appl..
[28] Ivo Iliev,et al. Online Digital Filter and QRS Detector Applicable in Low Resource ECG Monitoring Systems , 2008, Annals of Biomedical Engineering.
[29] N. Huang,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[30] Liang-Yu Shyu,et al. Using wavelet transform and fuzzy neural network for VPC detection from the holter ECG , 2004, IEEE Transactions on Biomedical Engineering.
[31] Lutgarde M. C. Buydens,et al. Using support vector machines for time series prediction , 2003 .
[32] Gregory T. A. Kovacs,et al. Robust Neural-Network-Based Classification of Premature Ventricular Contractions Using Wavelet Transform and Timing Interval Features , 2006, IEEE Transactions on Biomedical Engineering.
[33] Pablo Laguna,et al. A wavelet-based ECG delineator: evaluation on standard databases , 2004, IEEE Transactions on Biomedical Engineering.
[34] Marcelo R. Risk,et al. Beat detection and classification of ECG using self organizing maps , 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).
[35] W.J. Tompkins,et al. ECG beat detection using filter banks , 1999, IEEE Transactions on Biomedical Engineering.
[36] C. Koley,et al. Wavelet Aided SVM Analysis of ECG Signals for Cardiac Abnormality Detection , 2005, 2005 Annual IEEE India Conference - Indicon.
[37] A. Likas,et al. Electrocardiogram (ECG): Automated Diagnosis , 2006 .