Dynamic GNNs for Precise Seizure Detection and Classification from EEG Data

arXiv:2405.09568v1 Announce Type: cross
Abstract: Diagnosing epilepsy requires accurate seizure detection and classification, but traditional manual EEG signal analysis is resource-intensive. Meanwhile, automated algorithms often overlook EEG's geometric and semantic properties critical for interpreting brain activity. This paper introduces NeuroGNN, a dynamic Graph Neural Network (GNN) framework that captures the dynamic interplay between the EEG electrode locations and the semantics of their corresponding brain regions. The specific brain region where an electrode is placed critically shapes the nature of captured …

abstract algorithms analysis arxiv automated brain brain activity classification cs.lg data detection dynamic eeg eess.sp epilepsy framework gnn gnns graph graph neural network network neural network paper semantic signal type