Wavelet-based texture analysis of EEG signal for prediction of epileptic seizures

Arthur Petrosian, Richard Homan, Suryalakshmi Pemmaraju, Sunanda Mitra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Electroencephalographic (EEG) signal texture content analysis has been proposed for early warning of an epileptic seizure. This approach was evaluated by investigating the interrelationship between texture features and basic signal informational characteristics, such as Kolmogorov complexity and fractal dimension. The comparison of several traditional techniques, including higher-order FIR digital filtering, chaos, autoregressive and FFT time-frequency analysis was also carried out on the same epileptic EEG recording. The purpose of this study is to investigate whether wavelet transform can be used to further enhance the developed methods for prediction of epileptic seizures. The combined consideration of texture and entropy characteristics extracted from subsignals decomposed by wavelet transform are explored for that purpose. Yet, the novel neuro-fuzzy clustering algorithm is performed on wavelet coefficients to segment given EEG recording into different stages prior to an actual seizure onset.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsAndrew F. Laine, Michael A. Unser, Mladen V. Wickerhauser
Pages189-194
Number of pages6
Edition1/-
StatePublished - 1995
EventWavelet Applications in Signal and Image Processing III. Part 1 (of 2) - San Diego, CA, USA
Duration: Jul 12 1995Jul 14 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Number1/-
Volume2569
ISSN (Print)0277-786X

Conference

ConferenceWavelet Applications in Signal and Image Processing III. Part 1 (of 2)
CitySan Diego, CA, USA
Period07/12/9507/14/95

Fingerprint Dive into the research topics of 'Wavelet-based texture analysis of EEG signal for prediction of epileptic seizures'. Together they form a unique fingerprint.

  • Cite this

    Petrosian, A., Homan, R., Pemmaraju, S., & Mitra, S. (1995). Wavelet-based texture analysis of EEG signal for prediction of epileptic seizures. In A. F. Laine, M. A. Unser, & M. V. Wickerhauser (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (1/- ed., pp. 189-194). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2569 , No. 1/-).