Towards Modality-Agnostic Seizure Classification: A Unified Deep Learning Framework for Heterogeneous EEG and Intracranial EEG Signals
A new framework of multimodal seizure classification integrating the heterogeneous EEG and iEEG recordings from different subjects and sources is presented, using the EEGNet-Vision Transformer as the feature extraction and classification network to learn the local discriminative patterns as well as global contextual in...