Classification of electrocardiogram signals with support vector machines and genetic algorithms using power spectral features

Biomedical Signal Processing and Control

Volumn 5, Issue 4, 2010, Pages 252-263

  Khazaee, A ^a   Ebrahimzadeh, A ^a  

^a BABOL NOSHIRVANI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

ECG beat classification; Genetic algorithm; Multitaper method; Non parametric PSD estimation methods; Parameter optimization; SVM

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISEASES; ELECTROCARDIOGRAPHY; EXTRACTION; FEATURE EXTRACTION; GENETIC ALGORITHMS; PARAMETER ESTIMATION; POWER SPECTRAL DENSITY; SPECTRAL DENSITY; SUPPORT VECTOR MACHINES;

ECG BEAT CLASSIFICATIONS; ELECTROCARDIOGRAM SIGNAL; ESTIMATION METHODS; GAUSSIAN RADIAL BASIS FUNCTIONS; HYBRID GENETIC ALGORITHMS; MULTITAPER METHODS; PARAMETER OPTIMIZATION; POWER SPECTRAL DENSITIES (PSD);

BIOMEDICAL SIGNAL PROCESSING;

ARTICLE; CONTROLLED STUDY; ELECTROCARDIOGRAM; GENETIC ALGORITHM; HEART ARRHYTHMIA; HEART BEAT; HEART LEFT BUNDLE BRANCH BLOCK; HEART RIGHT BUNDLE BRANCH BLOCK; HEART VENTRICLE EXTRASYSTOLE; HUMAN; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; POWER SPECTRUM; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; SUPRAVENTRICULAR PREMATURE BEAT;

EID: 77956651195     PISSN: 17468094     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.bspc.2010.07.006     Document Type: Article

References (31)

1. G.D. Clifford, F. Azuaje, and P.E. McShary Advanced Methods and Tools for ECG Data Analysis 2006 Artech House Norwood, MA
2. M.S. Thaler The Only EKG Book You'll Ever Need third ed. 1999 Lippincott/Williams & Wilkins Philadelphia, PA/Baltimore, MD
3. L.Y. Shyu, Y.H. Wu, and W.C. Hu Using wavelet transform and fuzzy neural network for VPC detection from the Holter ECG IEEE Trans. Biomed. Eng. 51 2004 1269 1273
4. O.T. Inan, L. Giovangrandi, and G.T.A. Kovacs Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features IEEE Trans. Biomed. Eng. 53 2006 2507 2515
5. A. Ebrahimzadeh, and A. Khazaee Detection of premature ventricular contractions using MLP neural networks: a comparative study Measurement 43 2010 103 112
6. S.N. Yu, and K.T. Chou Selection of significant for ECG beat classification Expert Syst. Appl. 36 2009 2088 2096
7. T. Ince, S. Kiranyaz, and M. Gabbouj A generic and robust system for automated patient-specific classification of electrocardiogram signals IEEE Trans. Biomed. Eng. 56 2009 1415 1426
8. U.R. Acharya Automatic identification of cardiac health using modeling techniques: a comparative study Inform. Sci. 178 2008 4571 4582
9. C.H. Lin Frequency-domain features for ECG beat discrimination using grey relational analysis-based classifier Comput. Math. Appl. 55 2008 680 690
10. R.R. Sarvestani, R. Boostani, and M. Roopaei VT and VF classification using trajectory analysis Nonlinear Anal. 71 2009 e55 e61
11. S. Osowski, and T.H. Linh ECG beat recognition using fuzzy hybrid neural network IEEE Trans. Biomed. Eng. 48 2001 1265 1271
12. E.D. Ubeyli Recurrent neural networks employing Lyapunov exponents for analysis of ECG signals Expert Syst. Appl. 37 2010 1192 1199
13. P. Chazal, M. O'Dwyer, and R.B. Reilly Automatic classification of heartbeats using ECG morphology and heartbeat interval features IEEE Trans. Biomed. Eng. 51 2004 1196 1206
14. M. Lagerholm Clustering ECG complexes using Hermite functions and self-organizing maps IEEE Trans. Biomed. Eng. 47 2000 839 847
15. L. Khadra, A.S. Al-Fahoum, and S. Binajjaj A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques IEEE Trans. Biomed. Eng. 52 2005 1840 1845
16. R.V. Andreao, B. Dorizzi, and J. Boudy ECG signal analysis through hidden Markov models IEEE Trans. Biomed. Eng. 53 2006 1541 1549
17. R. JoyMartis, C. Chakraborty, and A.K. Ray A two-stage mechanism for registration and classification of ECG using Gaussian mixture model Pattern Recognit. 42 2009 2979 2988
18. S. Mitra, M. Mitra, and B.B. Chaudhuri A rough set-based inference engine for ECG classification IEEE Trans. Instrum. Meas. 55 2006 2198 2206
19. F. de Chazal, and R.B. Reilly A patient adapting heart beat classifier using ECG morphology and heartbeat interval features IEEE Trans. Biomed. Eng. 53 2006 2535 2543
20. S. Osowski, T. Markiewicz, and L.T. Hoai Recognition and classification system of arrhythmia using ensemble of neural networks Measurement 41 2008 610 617
21. V. Vapnik Statistical Learning Theory 1998 Wiley New York
22. S.V. Vaseghi Advanced Digital Signal Processing and Noise Reduction 4th edition 2008 John Wiley & Sons
23. P.D. Welch The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms IEEE Trans. Audio Electroacoust. AU-15 June 1967 70 73
24. D.B. Percival, and A.T. Walden Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques 1993 Cambridge University Press Cambridge, UK 611 pp
25. C. Burges A tutorial on support vector machines for pattern recognition Data Mining Knowl. Discov. 2 1998 121 167 (Pubitemid 128695475)
26. C. Cortes, and V. Vapnik Support vector networks Mach. Learn. 20 3 1995 273 297
27. K.R. Muller, S. Mika, G. Ratsch, K. Tsuda, and B. Scholkopf An introduction to kernel-based learning algorithms IEEE Trans. Neural Netw. 12 March (2) 2001 181 202
28. S. Sumathi, T. Hamsapriya, and P. Surekha Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab 2008 Springer-Verlag Berlin Heidelberg
29. S. Bandyopadhyay, and S.K. Pal Classification and Learning Using Genetic Algorithms 2007 Springer-Verlag Berlin Heidelberg
30. R.G. Mark, G.B. Moody, MIT-BIH Arrhythmia Database 1997 [Online]. Available: http://ecg.mit.edu/dbinfo.html.
31. G.B. Moody, and R.G. Mark The impact of the MIT/BIH arrhythmia database IEEE Eng. Med. Biol. Mag. 20 May-June (3) 2001 45 50