The influence of information about the circumstances of EEG recordings on the ability to identify seizure patterns.

Purpose To quantify the influence of prior knowledge about the patient and the EEG circumstances on the EEG-based seizure detection rate. Methods A sample of 95 EEGs with epileptic seizure patterns matched with 95 seizure-free control sequences were extracted from EEG video monitoring data. They were stripped of all additional information. These plain EEG recordings were evaluated by two board certified EEG reviewers. The results were compared with the interpretations of the original video monitoring evaluations. Results Using the plain EEG sequences, epileptic seizure patterns were detected with a sensitivity and specificity of 0.758 and 0.958, respectively. The classification of the seizure pattern localization and lateralization differed in 56% and 50%, respectively, from the results of the video monitoring evaluations. Conclusion Additional information about the patient and the events during an EEG recording leads to a clinically and statistically significant increase in the seizure detection rates. These results imply that the human evaluation of a plain EEG without further information may not be seen as the gold standard in EEG evaluation. The performance estimation of automated EEG evaluation methods should take this into account.