Brain Advance Access originally published online on September 23, 2003
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Brain, Vol. 126, No. 12, 2616-2626,
December 2003
© 2003 Guarantors of Brain
doi: 10.1093/brain/awg265
How well can epileptic seizures be predicted? An evaluation of a nonlinear method
1 Epilepsy Centre and 2 Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
Correspondence to: Dr Andreas Schulze-Bonhage, Epilepsy Centre, University of Freiburg, Breisacher Strasse 64, 79106 Freiburg, Germany E-mail: schulzeb{at}nz.ukl.uni-freiburg.de
The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A nonlinear feature motivated by the correlation dimension is a seemingly promising approach. In a previous study this method was reported to identify ‘preictal dimension drops’ up to 19 min before seizure onset, exceeding the variability of interictal data sets of 30–50 min duration. Here we have investigated the sensitivity and specificity of this method based on invasive long-term recordings from 21 patients with medically intractable partial epilepsies, who underwent invasive pre-surgical monitoring. The evaluation of interictal 24-h recordings comprising the sleep–wake cycle showed that only one out of 88 seizures was preceded by a significant preictal dimension drop. In a second analysis, the relation between dimension drops within time windows of up to 50 min before seizure onset and interictal periods was investigated. For false-prediction rates below 0.1/h, the sensitivity ranged from 8.3 to 38.3% depending on the prediction window length. Overall, the mean length and amplitude of dimension drops showed no significant differences between interictal and preictal data sets.
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