AI-Driven Electrographic Seizure Classification and Seizure Onset Detection Using Image- and Time-Series-Based Approaches.

Journal: IEEE transactions on bio-medical engineering
Published Date: Jul 31, 2025

Abstract

OBJECTIVE: Manually distinguishing between seizure and non-seizure events in intracranial electroencephalography (iEEG) recordings is highly time-consuming. In this study, we explored AI-based approaches for electrographic seizure classification (ESC) and seizure onset detection (SOD) in treatment-resistant epilepsy patients. ESC involves distinguishing seizure events from non-seizure activity, while SOD focuses on pinpointing the exact moment a seizure begins.

Authors

  • Muhammad Furqan Afzal
  • Sharanya Arcot Desai
  • Wade Barry
  • Jonathan Kuo
  • Shawna W Benard
  • Christopher B Traner
  • Erik J Kobylarz
  • Thomas K Tcheng
  • David Greene
  • Cairn Seale
  • Martha J Morrell

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