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.

Published on January 2018

EBioMedicine

Access: Open

View publication

More research