Objective

Identification of consistent distinguishing features between preictal and interictal periods in the EEG is an essential step towards performing seizure prediction. We propose a novel method to separate preictal and interictal states based on the analysis of the high frequency activity of intracerebral EEGs in patients with mesial temporal lobe epilepsy.

Methods

Wavelet energy and entropy were computed in sliding window fashion from preictal and interictal epochs. A comparison of their organization in a 2 dimensional space was carried out using three features quantifying the similarities between their underlying states and a reference state. A discriminant analysis was then used in the features space to classify epochs. Performance was assessed based on sensitivity and false positive rates and validation was performed using a bootstrapping approach.

Results

Preictal and interictal epochs were discriminable in most patients on a subset of channels that were found to be close or within the seizure onset zone.

Conclusions

Preictal and interictal states were separable using measures of similarity with the reference state. Discriminability varies with frequency bands.

Significance

This method is useful to discriminate preictal from interictal states in intracerebral EEGs and could be useful for seizure prediction.