Simultaneous spike detection and topographic classification in pediatric surface EEGs

In this study, an algorithm is introduced for the automatic detection and simultaneous topographic classification of interictal regional spike activity in pediatric surface EEG records. The algorithm is based on the classification of the topographic distribution of instantaneous power by means of a 'group' trained classifier. The results of automatic spike analysis were compared with the decisions of two experienced electroencephalographers. Four routine EEG records exhibiting (multi)regional spikes were examined. The mean selectivity for the automatic spike detector was 84.6% (mean sensitivity 88.1%, mean specificity 89.3%) and for the electroencephalographers 85.3%. All spikes detected by the algorithm were simultaneously classified according to their topographic characteristics. The results of automatic spike classification (lateralization/localization) corresponded to the results of visual analysis.