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In 12 epileptic patients suffering from "absences" 8-channel EEG was recorded by telemetry. The autoregressive model was applied to the signal and the prediction coefficients being the basis for calculation of the poles of the predictor. The location of the poles in the z- and s-planes was described as a function of time for 0.1 s steps along the pre-seizure EEG. In 10 of the 12 patients, and in 25 of the 28 recorded seizures this presentation of the poles of the predictor showed specific pattern linked with the occurrence of the seizure. The trajectory of the "most mobile pole" during the pre-seizure period could aid in the prediction of the seizure by several seconds.

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Multivariate spectral estimation based on parametric modelling has been applied to epileptic surface EEG in order to detect EEG changes that occur prior to the clinical outbreak of the seizure. A better time/frequency resolution has been achieved using residual energy ratios (Dickinson's method). Prediction of oncoming seizures was based on detection of increased preictal synchronisation by calculation of coherence and pole trajectories. The method has been tested on simulated EEG data and on real EEG data from patients with primary generalised epilepsy. Prediction times of 1-6 s have been found in several seizures from five patients.