Epileptic seizure prediction using big data and deep learning: Toward a mobile system

Abstract

This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance.

Authors

Isabell Kiral-Korneka, Subhrajit Roya, Ewan Nurse, Benjamin Mashford, Philippa Karoly, Thomas Carroll, Daniel Payne, Susmita Saha, Steven Baldassano, Terence O’Brien, David Grayden, Mark Cook, Dean Freestone, and Stefan Harrer.