Analysis of scalp EEG for epileptic seizure prediction

Results in literature show that the convergence of the Short-Term Maximum Lyapunov Exponent (STLmax) time series, extracted from intracranial EEG recorded from patients affected by intractable temporal lobe epilepsy, is linked to the seizure onset. According to these results, when the STLmax profiles of different electrode sites converge and reach a critical convergence level, a seizure is likely to occur. This prediction technique was here implemented and tested over three scalp EEG recordings: one from a patient affected by partial frontal lobe epilepsy and two from a patient affected by absence seizures. The technique succeeded in predicting each one of the predictable seizures, with an average prediction horizon of 5.43 min. The technique also detected a critical area that coincided with the focus, for the patient with focal epilepsy, and with the frontal area, for the patient affected by absence seizures. Moreover, this was the first study of predictability that included generalized seizures