Application of time frequency and wavelet analysis to the diagnosis of epilepsy

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.

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