Abstract
Records of brain electrical activity from depth and scalp electrodes are used to localize the origin of seizure discharges in epileptic patients who are candidates for surgical removal of the seizure focus. In clinical practice, the epileptogenic loci is infered from visual analysis of the interictal and ictal discharges. Automated systems may be used to detect signal epochs that contain transients, patterns, and characteristic features of abnormal conditions. There are two basic areas of clinical application: 1) an automatic system for data reduction in long-term EEG; or 2) as a short-term detector of epileptic transients. Several techniques have been applied in order to solve the problem of computer assisted detection of epileptiform transients as previously mentioned by Blanco et al. in this book and others including template matching [11], parametric [1], mimetic [8] and syntactic [32] methods, neural networks [10], expert systems [12], phase-space topography [14], wavelet transforms [22, 23], and recently, polynomial spline and multiresolution frameworks [21].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
K. Arakawa, D. Fender, H. Harashima, H. Miyakawa, and Y. Saitoh. Separation of a nonstationary component from the EEG by a nonlinear digital filter. IEEE Trans. Biomed. Eng.,33:724–726, 1986.
A. Babloyantz. Evidence of chaotic dynamics of brain activity during the sleep cycle. In Meyer Kress, editor, Dimensions and Entropies in Chaotics Systems, pages 241–245, Springer Verlag, Berlin, 1986.
E. Basar. Chaos in Brain Function. Springer Verlag, Berlin, 1990.
S. Blanco, C. D’Attellis, S. Isaacson, O. Rosso, and R. Sirne. Time-frequency analysis of EEG series (ii): comparison between methods based on gabor and wavelets transforms. Physical Rev. E, Vol. 54, No. 5, 1996.
C. K. Chui. An Introduction to Wavelets. Academic Press, San Diego, 1992.
C. E. D’Attellis, S. I. Isaacson, and R. O. Sirme. Detection of epileptic events in EEG using wavelet theory. To appear in Annals of Biomédical Engineering.
I. Daubechies. Ten Lectures on Wavelets. Siam, Philadelphia, USA, 1992.
P. Guedes de Oliveira, C. Queiroz, and F. Lopes de Silva. Spike detection based on a pattern recognition approach using a microcomputer. Electroenceph. Clin. Neorophysiol, 56:97–103, 1983.
A. Dingle, R.D. Jones, G.J. Carroll, and W.R. Pright. A multistage system to detect epileptiform activity in the EEG. IEEE Trans. Biomed. Eng.,40:1260–1268, 1993.
R.C. Eberhart, R.W. Dobbins, and W.R. Webber. Eeg waveform analysis using case-net. Proc. Conf. IEEE Eng. Med. Biol Soc, 2046–2047, 1989.
G. Fischer, N.J.I. Mars, and F. Lopes da Silva. Pattern recognition of epileptiform transients in the electroencephalogram. Inst. Med. Physi, Rep. 7, Utrecht, 1980.
J.R. Glover, D.N. Varmazis, and P.Y. Ktonas. Continued development of a knowledge-based system to detect epileptogenic sharp transients in the EEG. Proc. Conf. IEEE Eng. Med. Biol. Soc, 1374–1375, 1990.
L.D. Iasemidis, J. C. Sackellares, H.P. Zaveri, and W.J. Williams. Modelling of ecog in temporal lobe epilepsy. 25th Ann. Rocky Mountain Bioing. Symposium, 1201–1203, 1988.
L.D. Iasemidis, J. C. Sackellares, H.P. Zaveri, and W.J. Williams. Phase space topography and the lyapunov exponent of electrocorticograms in partial seizures. Brain Topogr.,2(3):187–201, 1990.
S. Kochen, C. D’Attellis, R. Sirne S. Isaacson, P. Salgado, O. Rosso, C. Parpaglione, and L. Riquelme. Seizure localization using gabor transform, wavelet analysis and neural networks in depth EEC Annual Meeting American Epilepsy Soc. New Orleans, 4–6, 1994.
Y. Meyer. Ondelettes. Hermann Ed, Paris, France, 1990.
Y. Meyer. Wavelets, Algorithms and Applications. SIAM, Philadelphia, USA, 1993.
G. Meyer-Kress and S.C. Layne. Dimensionality of human electroencephalogram. In M. F. Shlesinger S. H. Koslow, A. J. Man-del, editor, Perspectives in Biologycal Dynamics and Theoretical Medicine, Ann. N.Y. Acad. Sci 504, New York, USA, 1987.
Y. B. Pesin. Characterisctic lyapunov exponents and smooth ergodic theory. Russ. Math. Surv, 32(4):55–114, 1977.
J. P. Pijn and F. H. Lopez da Silva. Propagation of electrical activity: nonlinear associations and time delays between EEG signals. Birkhäuser, Boston, 1993.
J. F. Schiff, A. Aldroubi, M. Unser, and S. Sato. Fast wavelet transformation of EEG. Electroencelography and Clinical Neu-rophysiology, 91:442–455, 1994.
L. Senhadji, G. Carrault, and J. J. Bellanger. Detection et cartographie multi-échelles en EEG, pages 609–614. Editions Frontières, Paris, 1993.
L. Senhadji, G. Carrault, J.J. Bellanger, and G. Passarello. Quelques nouvelles applications de la transformée en ondelettes. Innov. Tech. Biol. Med.,14:389–403, 1993.
C. E. Shannon. A mathematical theory of comunication. The Bell System Technical Journal, 27(3):379–423, 1948.
F. Takens. Detecting strange attractors in turbulence, pages 366–381. Berlin, 1981.
J. M. Thompson and Stewart. Non linear Dynamics and Chaos. Wiley and Sons, 1993.
M. Torres, L. Gamero, and E. D’Attellis. Detection of changes in Nonlinear dynamical systems using Multirresolution Entropy. Technical Report 2812, INRIA-Rapport de recherche, 1996.
M. Torres, L. Gamero, and E. D’Attellis. A multirresolution entropy approach to detect epileptic form activity in the EEG. In I. Pitas, editor, IEEE Workshop on non linear signal and image processing, pages 791–794, 1995.
M. Torres, L. Gamero, and E. D’Attellis. Pattern detection in EEG using multirresolution entropy. Latin American Applied Research, (53):53–57, 1995.
M. Unser. Fast Gabor-like windowed Fourier and continuous wavelet transform. IEEE Signal Process. Letters, (l):76–79, 1994.
M. Unser, A. Aldroubi, and M. Eden. A family of polynomial spline wavelet transforms. Signal Process.,30:141–162, 1993.
R. Walters, J. Principe, and S. Park. Spike detection using a syntactic pattern recognition approach. In IEEE Eng. Med. Biol. Soc, pages 1810–1811, 1989.
B. J. West. Fractal Physiology and Chaos in Medicine, Nonlinear Phenomena in Life Science. Volume I, World Scientific, Singapore, 1990.
B. J. West and Patterns. Information and Chaos in Neuronal Systems, Nonlinear Phenomena in Life Science, chapter II. World Scientific, Singapore, 1993.
A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano. Determining Lyapunov exponents from a time series. Physica D, 16:285–317, 1985.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
D’Attellis, C.E., Gamero, L.G., Isaacson, S.I., Sirne, R.O., Torres, M.E. (1997). Characterization of Epileptic EEG Time Series (II): Wavelet Transform and Information Theory. In: D’Attellis, C.E., Fernández-Berdaguer, E.M. (eds) Wavelet Theory and Harmonic Analysis in Applied Sciences. Applied and Numerical Harmonic Analysis. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-2010-7_10
Download citation
DOI: https://doi.org/10.1007/978-1-4612-2010-7_10
Publisher Name: Birkhäuser, Boston, MA
Print ISBN: 978-1-4612-7379-0
Online ISBN: 978-1-4612-2010-7
eBook Packages: Springer Book Archive