Seizure forecasting using a novel sub-scalp ultra-long term EEG monitoring system

Abstract

Accurate recognition of seizure activity is essential for diagnostic, management and forecasting purposes, but patient-reported seizures have been shown to be unreliable. Earlier work has revealed accurate capture of electrographic seizures and forecasting is possible with an implantable intracranial device, but less invasive electroencephalography (EEG) recording systems would be optimal. Here, we present preliminary results of seizure detection and forecasting with a minimally invasive sub-scalp device that continuously records EEG.

Authors

Rachel E. Stirling, Matias I. Maturana, Philippa J. Karoly, Ewan S. Nurse, Kate McCutcheon, David B. Grayden, Steven G. Ringo, John M. Heasman, Rohan J. Hoare, Alan Lai, Wendyl D’Souza, Udaya Seneviratne, Linda Seiderer, Karen J. McLean, Kristian J. Bulluss, Michael Murphy, Benjamin H. Brinkmann, Mark P. Richardson, Dean R. Freestone, and Mark J. Cook.