Abstract: Systems, methods and programs for processing EEG data for display and/or automatically detecting a seizure in a patient based on one or more spectrograms created from the EEG data. EEG data from a patient may be paired into channels based on electrode locations. Spectrograms are generated from EEG data from channels, respectively. The spectrograms of different channels are grouped and a median power spectrogram (MPS) is calculated for the group. The MPS may be used to automatically determine whether the patient had a seizure by applying a machined learned model (ML) model. The ML model is trained and tested using historical EEG data from a plurality of patients. The MPS or a relationship between a plurality of MPS of different groups may be displayed on a bedside monitor in real-time for viewing by a bedside clinician.