Temporal variability of the ECoG signal during epileptic seizures

Temporal characteristics of the EEG have been extensively studied for their relationship to both sleep and epilepsy. In this work we introduce a computational algorithm that quantifies temporal variability of the EEG signal based on the local minima and the local maxima of the signal. The proposed computational algorithm is applied to examine the temporal variability of an ECoG signal obtained from a subject with epilepsy. The computational results show that during an epileptic seizure the features generated by the algorithm have distinguishable characteristics corresponding to different states of the brain, suggesting that the proposed algorithm may be potentially useful for epileptic seizure detection.