Detection and Assessment of Encephalitis from EEG

Inflammatory brain diseases have been associated to the presence of slow biphasic complexes (SBC)in the EEG. An automated method has been developed to identify them. A dataset of 128 EEGs was recorded from pediatric controls and patients showing encephalitis with different levels of severity. Experts assigned a severity score with 5 levels to each trace, considering both electrophysiological and clinical manifestations. The number, amplitude and location of SBCs were used to identify automatically the severity scores using a binary classification decision tree. True classifications have been obtained in the 64.1 % of cases (55.6% using a leave-one-out approach)and misclassifications were among close severity scores (about 80 % of accuracy was obtained considering 3 instead of 5 severity scores), indicating that SBCs may support the identification, assessment and follow-up of encephalitis.