Evolutionary model selection in a wavelet-based support vector machine for automated seizure detection

Expert Systems with Applications

Volumn 38, Issue 9, 2011, Pages 10751-10758

  Zavar, M ^a   Rahati, S ^b   Akbarzadeh T, M R ^c   Ghasemifard, H ^d  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

^c FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

^d MASHHAD UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

ECG; Genetic algorithm; Model selection; Partial seizure; Support vector machines; Wavelet kernel function

Indexed keywords

ACCURACY RATE; CLASSIFICATION ACCURACY; CLASSIFICATION TECHNIQUE; DATA SETS; ECG; EVOLUTIONARY MODELS; INPUT FEATURES; LYAPUNOV EXPONENT; MASSACHUSETTS INSTITUTE OF TECHNOLOGY; MODEL SELECTION; PARTIAL EPILEPSY; PARTIAL SEIZURE; SEIZURE DETECTION; STATISTICAL LEARNING THEORY; WAVELET ENTROPIES; WAVELET KERNEL FUNCTION;

CLASSIFICATION (OF INFORMATION); ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; FEATURE EXTRACTION; FRACTAL DIMENSION; GEARS; GENETIC ALGORITHMS; LYAPUNOV METHODS; MATHEMATICAL MODELS; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 79955594660     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.01.087     Document Type: Article

References (24)

1. I.C. Al-Aweel, K.B. Krishnamurthy, J.M. Hausdorff, J.E. Mietus, J.R. Ives, and A.S. Blum Postictal heart rate oscillations in partial epilepsy Neurology 53 7 1999 1590 1592 (Pubitemid 29491962)
2. E. Avci Selecting of the optimal feature subset and kernel parameters in digital modulation classification by using hybrid genetic algorithm-support vector machines: HGASVM Expert Systems with Applications 2008 1 12
3. C.J.C. Burges A tutorial on support vector machines for pattern recognition Data Mining and Knowledge Discovery 2 1998 121 167 (Pubitemid 128695475)
4. C. Cortes, and V. Vapnik Support vector networks Machine Learning 20 3 1995 273 297
5. Cui, W. Z. (2006). Wavelet support vector machine with universal approximation and its application. In IEEE information theory workshop (pp. 340-364).
6. S.Y. Foo, G. Stuart, B. Harvey, and A. Meyer-Baese Neural network-based EKG pattern recognition Engineering Applications of Artificial Intelligence 15 2002 253 260 (Pubitemid 35412472)
7. I. Güler, and E.D. Übeyli Application of adaptive neuro-fuzzy inference system for detection of electrocardiographic changes in patients with partial epilepsy using feature extraction Expert Systems with Applications 27 3 2004 323 330
8. I. Güler, and E.D. Übeyli An expert system for detection of electrocardiographic changes in patients with partial epilepsy using wavelet-based neural networks Expert Systems with Application 22 2 2005 62 71 (Pubitemid 43906634)
9. J. Hirsch, and C.O.a.L. Ictal heart rate differentiates epileptic from non-epileptic seizures Neurology 58 2002 636 638
10. N. Hitiris, S. Suratman, K. Kelly, L.J. Stephen, G.J. Sills, and M.J. Brodie Sudden unexpected death in epilepsy: A search for risk factors Epilepsy & Behavior 10 2007 138 141 (Pubitemid 46132182)
11. H. Leung, P. Kwan, and C.E. Elger Finding the missing link between ictal bradyarrhythmia, ictal asystole, and sudden unexpected death in epilepsy Epilepsy & Behavior 13 2006 19 30 (Pubitemid 44028772)
12. F. Leutmezer, C. Schernthaner, S. Lurger, K. Pötzelberger, and C. Baumgartner Electrocardiographic changes at the onset of epileptic seizures Epilepsia 44 3 2003 348 354 (Pubitemid 36343765)
13. P. Paramanathan, and R. Uthayakumar Application of fractal theory in analysis of human electroencephalographic signals Computers in Biology and Medicine 38 2008 372 378
14. O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, and M. Schurmann Wavelet entropy: A new tool for analysis of short duration brain electrical signals Journal of Neuroscience Methods 105 2000 65 75 (Pubitemid 32106919)
15. S.EL. Safty, and A.E.-Z. Applying wavelet entropy principle in fault classification Expert Systems with Applications 30 2008 1307 6884
16. S.C. Saxena, V. Kumar, and S.T. Hamde Feature extraction from ECG signals using wavelet transforms for disease diagnostics International Journal of Systems Science 33 13 2002 1073 1085
17. C. Stollberger, and J. Finsterer Cardiorespiratory findings in sudden unexplained/unexpected death in epilepsy (SUDEP) Epilepsy Research 59 2004 51 60 (Pubitemid 38595421)
18. E.D. Übeyli, and I. Güler Detection of electrocardiographic changes in partial epileptic patients using Lyapunov exponents with multilayer perceptron neural networks Engineering Applications of Artificial Intelligence 17 6 2004 567 576
19. E.D. Übeyli, and I. Güler Support vector machines for detection of electrocardiographic changes in partial epileptic patients Expert Systems with Applications 51 2008 1 8
20. V. Vapnik The nature of statistical learning theory (pp. 33-45) 1995 Springer New York
21. A. Widodo, and B.-S. Yang Wavelet support vector machine for induction machine fault diagnosis based on transient current signal Expert Systems with Applications 2007 1 10
22. M.H. Yang, and R.-C. Wang DDoS detection based on wavelet kernel support vector machine The Journal of China Universities of Posts and Telecommunications 15 3 2008 59 63
23. Zhang, X.; Ren, S.-J.; Xu, J.-H.; & Zhu, Z.-C. (2005). Robust multiwavelets support vector regression network. In International conference on control and automation (ICCA2005) WE-2.5 (pp. 1220-1224). (Pubitemid 41651699)
24. L. Zhang, W. Zhou, and L. Jiao Wavelet support vector machine IEEE 34 2004 34 39