Use of principal component analysis for automatic classification of epileptic EEG activities in wavelet framework

Expert Systems with Applications

Volumn 39, Issue 10, 2012, Pages 9072-9078

  Rajendra Acharya, U ^a   Vinitha Sree, S ^b   Alvin, Ang Peng Chuan ^a   Suri, Jasjit S ^b,c  

^a DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING   (Singapore)

^b Global Biomedical Technologies   (United States)

^c IDAHO STATE UNIVERSITY   (United States)

Author keywords

Classification; Eigenvalues; Electroencephalogram; Epilepsy; Ictal; Interictal; Non linear analysis; Principal component analysis; Wavelet Packet Decomposition

Indexed keywords

EIGENVALUES; EPILEPSY; ICTAL; INTERICTAL; PRINCIPAL COMPONENT ANALYSIS (PCA); WAVELET PACKET DECOMPOSITION;

CLASSIFICATION (OF INFORMATION); EIGENVALUES AND EIGENFUNCTIONS; OBSERVABILITY; PRINCIPAL COMPONENT ANALYSIS; WAVELET ANALYSIS; WAVELET TRANSFORMS;

ELECTROENCEPHALOGRAPHY;

EID: 84859217391     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.02.040     Document Type: Article

References (49)

1. U.R. Acharya, K.C. Chua, T.C. Lim, Dorithy, and J.S. Suri Automatic identification of epileptic EEG signals using nonlinear parameters Journal of Mechanics in Medicine and Biology 9 4 2009 539 553
2. U.R. Acharya, O. Faust, N. Kannathal, T.J. Chua, and S. Laxminarayan Non-linear analysis of EEG signals at various sleep stages Computer Methods and Programs in Biomedicine 80 1 2005 37 45
3. U.R. Acharya, S. Vinitha Sree, S. Chattopadhyay, W. Yu, and A.P.C. Alvin Application of recurrence quantification analysis for the automated identification of epileptic EEG signals International Journal of Neural Systems 21 3 2011 199 211
4. Acharya, U.R.; Vinitha Sree, S.; Chattopadhyay, S.; Ng, K.-H.; Suri, J.S. (2011b) Automated diagnosis of epileptic EEG using entropies. Biomedical Signal Processing and Control, doi:10.1016/j.bspc.2011.07.007.
5. H. Adeli, and S. Ghosh-Dastidar Automated EEG based diagnosis of neurological disorders: Inventing the future of neurology 2010 CRC Press
6. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr Alzheimer's disease and models of computation: Imaging, classification, and neural models Journal of Alzheimer's disease 7 3 2005 187 199
7. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr Alzheimer's disease: Models of computation and analysis of EEGs Clinical EEG and Neuroscience 36 3 2005 131 140
8. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr A wavelet-chaos methodology for analysis of EEGs and EEG sub-bands to detect seizure and epilepsy IEEE Transactions on Biomedical Engineering 54 2 2007 205 211
9. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease Neuroscience Letters 444 2 2008 190 194
10. H. Adeli, Z. Zhou, and N. Dadmehr Analysis of EEG records in an epileptic patient using wavelet transform Journal of Neuroscience Methods 123 1 2003 69 87
11. M. Ahmadlou, and H. Adeli Wavelet synchronization methodology: A new approach for EEG-based diagnosis of ADHD Clinical EEG and Neuroscience 41 1 2010 1 10
12. M. Ahmadlou, and H. Adeli Fuzzy synchronization likelihood with application to attention deficit hyperactivity disorder Clinical EEG and Neuroscience 42 1 2011 6 13
13. M. Ahmadlou, H. Adeli, and A. Adeli New diagnostic EEG markers of the Alzheimer's disease using visibility graph Journal of Neural Transmission 117 9 2010 1099 1109
14. M. Ahmadlou, H. Adeli, and A. Adeli Fractality and a wavelet-chaos-neural network methodology for EEG-based diagnosis of autistic spectrum disorder Journal of Clinical Neurophysiology 27 5 2010 328 333
15. M. Ahmadlou, H. Adeli, and A. Adeli Fractality and a wavelet-chao methodology for EEG-based diagnosis of Alzheimer's disease Alzheimer Disease and Associated Disorders 25 1 2011 85 92
16. Andrzejak, R.G.; Lehnertz, K.; Mormann, F.; Rieke, C.; David, P.; Elger, C.E. (2001). Indications of nonlinear deterministic and finite dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Physical Review, E64, 061907. < http://www.meb.uni- bonn.de/epileptologie/science/physik/eegdataold.html > Accessed August 2011.
17. D. Bai, T. Qiu, and X. Li The sample entropy and its application in EEG based epilepsy detection Journal of Biomedical Engineering 24 1 2007 200 205
18. K.C. Chua, V. Chandran, U.R. Acharya, and C.M. Lim Analysis of epileptic EEG signals using higher order spectra Journal of Medical and Engineering Technology 33 1 2009 42 50
19. K.C. Chua, V. Chandran, U.R. Acharya, and C.M. Lim Automatic identification of epileptic EEG signals using higher order spectra International Journal of Engineering in Medicine 223 4 2009 485 495
20. K.C. Chua, V. Chandran, U.R. Acharya, and C.M. Lim Application of higher order spectra to identify epileptic EEG Journal of Medical Systems 2010 10.1007/s10916-010-9433-z
21. O. Faust, U.R. Acharya, C.M. Lim, and B.H.C. Sputh Automatic identification of epileptic and background EEG signals using frequency domain parameters International Journal of Neural Systems 20 2 2010 159 176
22. S. Ghosh-Dastidar, and H. Adeli Improved spiking neural networks for EEG classification and epilepsy and seizure detection Integrated Computer-Aided Engineering 14 3 2007 187 212
23. S. Ghosh-Dastidar, and H. Adeli A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection Neural networks 22 2009 1419 1431
24. S. Ghosh-Dastidar, H. Adeli, and N. Dadmehr Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection IEEE Transactions on Biomedical Engineering 54 9 2007 1545 1551
25. S. Ghosh-Dastidar, H. Adeli, and N. Dadmehr Principal component analysis-enhanced cosine radial basis function neural network for robust epilepsy and seizure detection IEEE Transactions on Biomedical Engineering 55 2 2008 512 518
26. L.B. Good, S. Sabesan, S.T. Marsh, K.S. Tsakalis, and L.D. Iasemidis Control of synchronization of brain dynamics leads to control of epileptic seizures in rodents International Journal of Neural Systems 19 2009 173 196
27. N.F. Guler, E.D. Ubey, and I. Guler Recurrent neural network employing Lyapunov exponents for EEG signals classification Expert Systems with Applications 29 3 2005 506 514
28. J. Han, M. Kamber, and J. Pei Data mining: Concepts and techniques 2nd ed. 2005 Morgan Kaufmann
29. H.W. Ian, and F. Eibe Data mining: Practical machine learning tools and techniques 2005 Morgan Kaufmann
30. N. Kannathal, U.R. Acharya, C.M. Lim, Q. Weiming, M. Hidayat, and P.K. Sadasivan Characterization of EEG: A comparative study Computer Methods and Programs in Biomedicine 80 1 2005 17 23
31. K. Kannathal, C.M. Lim, U.R. Acharya, and P.K. Sadasivan Entropies for detection of epilepsy in EEG Computer Methods and Programs in Biomedicine 80 3 2005 187 194
32. D.T. Larose Discovering knowledge in data: An introduction to data mining 2004 Wiley Interscience New Jersey, USA ch.5
33. D.T. Larose Discovering knowledge in data: An introduction to data mining 2004 Wiley Interscience New Jersey, USA ch.6
34. K. Lehnertz Epilepsy and nonlinear dynamics Journal of Biological Physics 33 3-4 2008 253 266
35. H. Ocak Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy Expert Systems with Applications 36 2 2009 2027 2036
36. I. Osorio, and M.G. Frei Seizure abatement with single DC pulses: Is phase resetting at play? International Journal of Neural Systems 19 3 2009 149 156
37. J.P. Pijn, D.N. Velis, M.J. van der Heyden, J. DeGoede, C.W. van Veelen, and F.H. Lopes da Silva Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings Brain Topography 9 4 1997 249 270
38. Sadati, N.; Mohseni, H. R.; Magshoudi, A. (2006). Epileptic seizure detection using neural fuzzy networks. Proc. IEEE International Conference on Fuzzy Syst. Canada, 16-21 July 2006, pp. 596-600.
39. Z. Sankari, H. Adeli, and A. Adeli Intrahemispheric, interhemispheric and distal EEG coherence in Alzheimer's disease Clinical Neurophysiology 2011 10.1016/j.clinph.2010.09.008
40. Z. Sankari, and H. Adeli Probabilistic neural networks for EEG-based diagnosis of Alzheimer's disease using conventional and wavelet coherence Journal of Neuroscience Methods 197 1 2011 165 170
41. A. Shoeb, J. Guttag, T. Pang, and S. Schachter Non-invasive computerized system for automatically initiating vagus nerve stimulation following patient specific detection of seizures or epileptiform discharges International Journal of Neural Systems 19 3 2009 157 172
42. V. Srinivasan, C. Eswaran, and N. Sriraam Approximate entropy-based epileptic EEG detection using artificial neural networks IEEE Transactions on Information Technology in Biomedicine 11 3 2007 288 295
43. A. Subasi EEG Signal classification using wavelet feature extraction and a mixture of expert model Expert Systems with Applications 32 4 2007 1084 1093
44. A. Subasi, and M.I. Gursoy EEG Signal classification using PCA, ICA, LDA and support vector machine Expert Systems with Applications 37 12 2010 8659 8666
45. D.P. Subha, K.P. Joseph, U.R. Acharya, and C.M. Lim EEG signal processing: A survey Journal of Medical Systems 34 2 2010 10.1007/s10916-008- 9231-z
46. M. Sugeno Industrial applications of fuzzy control 1985 Elsevier Science Pub. Co
47. N.V. Thakor, and S. Tong Advances in quantitative electroencephalogram analysis methods Annual Reviews 6 2004 453 495
48. WHO. (2011). World Health Organization statistics on epilepsy. < http://www.who.int/mediacentre/factsheets/fs999/en/index.html > Accessed August 2011.
49. WPD. (2011). < http://www.mathworks.com/help/toolbox/wavelet/ug/f7- 1011118.html > Accessed August 2011.