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Proceedings Paper

Application of time frequency and wavelet analysis to the diagnosis of epilepsy
Author(s): Mingui Sun; Lin-Sen Pon; Mark L. Scheuer; Robert J. Sclabassi
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Paper Abstract

Wavelet transforms and time-frequency distributions are powerful techniques for analysis of nonstationary biomedical signals. This paper investigates three applications of these techniques to multichannel electroencephalography (EEG) for the diagnosis of epilepsy. Wavelet transforms are utilized to detect the onset of seizures at different sites of subdural electrodes, and to extract spike patterns from EEG data recorded from the scalp. Time-frequency distributions are applied to characterize the early activity of seizures.

Paper Details

Date Published: 5 April 2000
PDF: 10 pages
Proc. SPIE 4056, Wavelet Applications VII, (5 April 2000); doi: 10.1117/12.381682
Show Author Affiliations
Mingui Sun, Univ. of Pittsburgh (United States)
Lin-Sen Pon, Univ. of Pittsburgh (United States)
Mark L. Scheuer, Univ. of Pittsburgh (United States)
Robert J. Sclabassi, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 4056:
Wavelet Applications VII
Harold H. Szu; Martin Vetterli; William J. Campbell; James R. Buss, Editor(s)

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