Classification Control for Discrimination between Interictal Epileptic and Non – Epileptic Pathological EEG Events
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32926
Classification Control for Discrimination between Interictal Epileptic and Non – Epileptic Pathological EEG Events

Authors: Sozon H. Papavlasopoulos, Marios S. Poulos, George D. Bokos, Angelos M. Evangelou

Abstract:

In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.

Keywords: Cross-Correlation Methods, Diagnostic Test, Interictal Epileptic, LVQ1 neural network, Auto-Cross-Correlation Methods, chi-square test.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1079930

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1500

References:


[1] M.C. Brown, B.E. Levin, E. Ramsay, D.A. Katz, M.S. Duchowny, "Characteristics of patients with non-epileptic seizures," J Epilepsy, 1991, 4(5) pp. 225-229.
[2] H. Meierkord, R. Will, D.R. Fish, S.D. Shorvon, "The clinical features and prognosis of pseudoseizures diagnosed using video-EEG telemetry," Neurology, 1991, 41(10) pp. 1643-1646.
[3] V. Ramani, "Intensive monitoring of psychogenic seizures, aggression and dyscontrol syndromes," Adv. Neurol, 1986, 46(2), pp. 103-127.
[4] F.A. Gibbs, E.L. Gibbs, W.G. Lennox, "Electroencephalographic classification of epileptic patient and control subjects," Arch Neural Psychiatric, 1943, 50(2), pp. 111-128.
[5] V. Ramani, S. Whalen, R. Loewenson, "Ictal characteristics of pseudoseizures," Arch. Neurol., 1985, 42(9), pp. 1183-1187.
[6] C.D. Binnie, Long-term monitoring, Comprehensive Epileptology. New York: Raven Press, 1991, pp.88-110.
[7] J.J. Barry, O. Atzman, M.J. Morrell. "Discriminating between epileptic and non-epileptic events: the utility of hypnotic seizure induction," Epilepsia 2000, 41(1), pp. 81-84.
[8] T.S. Walczak, D.T. Williams, W. Berten, "Utility and reliability of placebo infusion in the evaluation of patients with seizures," Neurology 1994, 44(3), pp. 394-399.
[9] M. Poulos, F. Geogiacodis, V. Chrissicopoulos, A. Evangelou, "Diagnostic Test for the Discrimination between Interictal Epileptic and Non-Epileptic Pathological EEG Events using Auto-Cross-Correlation Methods," American Journal of Electroneurodiagnostic Technology, Dec 2003, v. 43, pp. 228-264.
[10] S. Papavlasopoulos, M. Poulos, A. Evangelou, "Feature Extraction from Interictal Epileptic and Non- Epileptic Pathological EEG Events for diagnostic Purposes using LVQ1 Neural Network," Proceedings of seventh International Conference on Mathematics Methods in Scattering Theory and Biomedical Technology, BIOTECH'7, 2005, Nimfaio, Greece.
[11] A. Medvedev, J.O. Willoughby, "Can hypersychronisation of fast (gamma) activity lead to generalized epilepticform discharges?" Proceedings, Epilepsy Society of Australia, 1999, 41.
[12] J.S. Barlow, "Methods of analysis of nonstationary EEGs with emphasis on segmentation techniques: a comparative review," Clin. Neurophysiology, 1985, 2(5) pp. 267 - 304.
[13] J.H. Zar, Biostatistical Analysis, New Jersey: Prentice-Hall, 1999, pp.72- 73.
[14] S. Haukin, Adaptive Filter Theory, New Jersey: Prentice Hall, 1996 pp. 136-138.
[15] N. Morrison, F. Donald, Multivariate Statistical Methods, New York: McGraw-Hill Book Company, 1976, pp.128-130
[16] J. A. Kangas, T. Kohonen, J. T. Laakson, "Variants of Self-Organizing Maps," IEEE Trans. Neural Networks, 1990, 1:1, pp. 93-99.
[17] F. Mormann, K. Lehnertz, R.G. Andrzejak, C.E. Elger, "Characterizing preictal states by changes in phase synchronization in intracranial EEG recordings from epilepsy patients," Epilepsia, 2000, 41(7), pp. 167-172.