Classification of EEG signals using neural network and logistic regression

Computer Methods and Programs in Biomedicine

Volumn 78, Issue 2, 2005, Pages 87-99

  Subasi, Abdulhamit ^a   Erçelebi, Ergun ^b  

^a KAHRAMANMARAS SUTCU IMAM UNIVERSITY   (Turkey)

^b GAZIANTEP UNIVERSITY   (Turkey)

Author keywords

EEG; Epileptic seizure; Lifting based discrete wavelet transform (LBDWT); Logistic regression (LR); Multilayer perceptron neural network (MLPNN)

Indexed keywords

ALGORITHMS; DISEASES; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; SIGNAL PROCESSING; STATISTICAL METHODS; WAVELET TRANSFORMS;

CLASSICAL WAVELET TRANSFORM (CWT); EPILEPTIC DISORDERS; EPILEPTIFORM DISCHARGES; LOGISTIC REGRESSION;

ELECTROENCEPHALOGRAPHY;

ACCURACY; ADULT; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; CHILD; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; FEMALE; HUMAN; LOGISTIC REGRESSION ANALYSIS; MALE; MATHEMATICAL COMPUTING; PHYSICIAN; RELIABILITY; ROC CURVE; SEIZURE; SIGNAL PROCESSING; STATISTICAL ANALYSIS; VELOCITY;

EID: 17744374301     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2004.10.009     Document Type: Article

References (41)

1. I. Guler, M.K. Kiymik, M. Akin, and A. Alkan AR spectral analysis of EEG signals by using maximum likelihood estimation Comput. Biol. Med. 31 2001 441 450
2. H. Adeli, Z. Zhou, and N. Dadmehr Analysis of EEG records in an epileptic patient using wavelet transform J. Neurosci. Methods 123 2003 69 87
3. O.A. Rosso, M.T. Martin, and A. Plastino Brain electrical activity analysis using wavelet-based informational tools Physica A 313 2002 587 608
4. N. Hazarika, J.Z. Chen, A.C. Tsoi, and A. Sergejew Classification of EEG signals using the wavelet transform Signal Process. 59 1 1997 61 72
5. S.V. Patwardhan, A.P. Dhawan, and P.A. Relue Classification of melanoma using tree structured wavelet transforms Comput. Methods Programs Biomed. 72 2003 223 239
6. M.L. Van Quyen, J. Foucher, J.P. Lachaux, E. Rodriguez, A. Lutz, J. Martinerie, and F.J. Varela Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony J. Neurosci. Methods 111 2001 83 98
7. S. Soltani, P. Simard, and D. Boichu Estimation of the self-similarity parameter using the wavelet transform Signal Process. 84 2004 117 123
8. R.Q. Quiroga, and M. Schurmann Functions and sources of event-related EEG alpha oscillations studied with the wavelet transform Clin. Neurophysiol. 110 1999 643 654
9. Z. Zhang, H. Kawabata, and Z.Q. Liu Electroencephalogram analysis using fast wavelet transform Comput. Biol. Med. 31 2001 429 440
10. E. Basar, M. Schurmann, T. Demiralp, C. Basar-Eroglu, and A. Ademoglu Event-related oscillations are 'real brain responses' - wavelet analysis and new strategies Int. J. Psychophysiol. 39 2001 91 127
11. A. Folkers, F. Mosch, T. Malina, and U.G. Hofmann Realtime bioelectrical data acquisition and processing from 128 channels utilizing the wavelet-transformation Neurocomputing 52-54 2003 247 254
12. O.A. Rosso, S. Blanco, and A. Rabinowicz Wavelet analysis of generalized tonic-clonic epileptic seizures Signal Process. 83 2003 1275 1289
13. V.J. Samar, A. Bopardikar, R. Rao, and K. Swartz Wavelet analysis of neuroelectric waveforms: a conceptual tutorial Brain Lang. 66 1999 7 60
14. Y.U. Khan, and J. Gotman Wavelet based automatic seizure detection in intracerebral electroencephalogram Clin. Neurophysiol. 114 2003 898 908
15. R.Q. Quiroga, O.W. Sakowitz, E. Basar, and M. Schurmann Wavelet transform in the analysis of the frequency composition of evoked potentials Brain Res. Protoc. 8 2001 16 24
16. A.B. Geva, and D.H. Kerem Forecasting generalized epileptic seizures from the eeg signal by wavelet analysis and dynamic unsupervised fuzzy clustering IEEE Trans. Biomed. Eng. 45 10 1998 1205 1216
17. E. Ercelebi Electrocardiogram signals de-noising using lifting-based discrete wavelet transform Comput. Biol. Med. 34 6 2004 479 493
18. E. Ercelebi Second generation wavelet transform-based pitch period estimation and voiced/unvoiced decision for speech signals Appl. Acoustics 64 2003 25 41
19. N. Pradhan, P.K. Sadasivan, and G.R. Arunodaya Detection of seizure activity in EEG by an artificial neural network: a preliminary study Comput. Biomed. Res. 29 1996 303 313
20. W. Weng, and K. Khorasani An adaptive structure neural network with application to EEG automatic seizure detection Neural Netw. 9 1996 1223 1240
21. J. Gotman Automatic recognition of epileptic seizures in the EEG Electroencephalogr. Clin. Neurophysiol. 54 1982 530 540
22. A. Petrosian, D. Prokhorov, R. Homan, R. Dashei, and D. Wunsch Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG Neurocomputing 30 2000 201 218
23. A.J. Gabor, R.R. Leach, and F.U. Dowla Automated seizure detection using a self-organizing neural network Electroencephalogr. Clin. Neurophysiol. 99 1996 257 266
24. E. Haselsteiner, and G. Pfurtscheller Using time-dependent neural Networks for EEG classification IEEE Trans. Rehab. Eng. 8 2000 457 463
25. B.O. Peters, G. Pfurtscheller, and H. Flyvbjerg Automatic differentiation of multichannel EEG signals IEEE Trans. Biomed. Eng. 48 2001 111 116
26. H. Qu, and J. Gotman A Patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: possible use as a warning device IEEE Trans. Biomed. Eng. 44 1997 115 122
27. C. Robert, J.F. Gaudy, and A. Limoge Electroencephalogram processing using neural Networks Clin. Neurophysiol. 113 2002 694 701
28. M. Sun, and R.J. Sclabassi The forward EEG solutions can be computed using artificial neural networks IEEE Trans. Biomed. Eng. 47 2000 1044 1050
29. W.R.S. Webber, R.P. Lesser, R.T. Richardson, and K. Wilson An approach to seizure detection using an artificial neural network (ANN) Electroencephalogr. Clin. Neurophysiol. 98 1996 250 272
30. W. Sweldens The lifting scheme: a custom-design construction of biorthogonal wavelets Appl. Comput. Harmon. Anal. 3 2 1996 186 200
31. W. Sweldens The lifting scheme: a construction of second generation wavelets SIAM J. Math. Anal. 29 2 1997 511 546
32. D.W. Hosmer, and S. Lemeshow Applied Logistic Regression 1989 Wiley New York
33. M. Schumacher, R. Robner, and W. Vach Neural networks and logistic regression: Part I Comput. Stat. Data Anal. 21 1996 661 682
34. W. Vach, R. Robner, and M. Schumacher Neural networks and logistic regression: part II Comput. Stat. Data Anal. 21 1996 683 701
35. M. Hajmeer, and M.I.A. Basheer Comparison of logistic regression and neural network-based classifiers for bacterial growth Food Microbiol. 20 2003 43 55
36. S. Dreiseitl, and L. Ohno-Machado Logistic regression and artificial neural network classification models: a methodology review J. Biomed. Inform. 35 2002 352 359
37. I.A. Basheer, and M. Hajmeer Artificial neural networks: fundamentals, computing, design, and application J. Microbiol. Methods 43 2000 3 31
38. B.B. Chaudhuri, and U. Bhattacharya Efficient training and improved performance of multilayer perceptron in pattern classification Neurocomputing 34 2000 11 27
39. L. Fausett Fundamentals of Neural Networks Architectures, Algorithms, and Applications 1994 Prentice Hall Englewood Cliffs, NJ
40. S. Haykin Neural Networks: A Comprehensive Foundation 1994 Macmillan New York
41. M.T. Hagan, and M.B. Menhaj Training feedforward networks with the Marquardt algorithm IEEE Trans. Neural Netw. 5 6 1994 989 993