EEG-based seizure prediction has undergone phases of optimism when analyses based on limited EEG samples suggested high sensitivity and specificity for several algorithms extracting features from raw preictal EEG data. When using long-term recordings, a more realistic view emerged which suggests that statistically significant predictions might be possible from surface and intracranial EEG, but no algorithm has yet demonstrated performance allowing for clinical application. Here, progress in EEG recording techniques, EEG analysis, and requirements for proper statistical validation of results are reported and discussed as they pertain to clinical implementation.
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