Automatic Detection of Epileptic Seizures with Recurrent and Convolutional Neural Networks

Abstract

Computer-aided diagnosis based on intelligent systems is an effective strategy to improve the efficiency of healthcare systems while reducing their costs. In this work, the epilepsy detection task is approached in two different ways, recurrent and convolutional neural networks, within a patient-specific scheme. Additionally, a detector function and its effects on seizure detection performance are presented. Our results suggest that it is possible to detect seizures from scalp EEGs with acceptable results for some patients, and that the DeepHealth framework is a proper deep learning software for medical research.