Automated Annotation of EEG in a Mouse Model of Epilepsy

The detection of epileptic seizure activity in EEG is important for the analysis and classification of epileptic seizures. However, as EEG is typically a dynamic and non-stationary process, it is timeconsuming for researchers to annotated manually. In this study, an automated system for the annotation of abnormal events in the EEGs from a mouse model of epilepsy is proposed. This will assist research groups to analyze abnormal events accurately and more efficiently.