Brain-Computer Interface

7Early Prediction of Epileptic Seizure Using Deep Learning Algorithm

T. Jagadesh¹*, A. Reethika¹, B. Jaishankar¹ and M.S. Kanivarshini²

¹Department of Electronics and Communication Engineering , KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India

²HCL Technologies, Chennai, Tamil Nadu, India

Abstract

Epilepsy is one of the most common neurological disorders in the world. Early expectation remains based on approach of seizures affects existence with epileptic patients. A novel patient-explicit seizure is defined in this article, expectation procedure dependent on profound learning and functional to extended haul scalp electroencephalograms (EEG) chronicles is proposed. The main objective is to recognize the preictal mind state besides separate it from predominant at the state of interictal at the correct time as could be expected and make it reasonable for continuous. In this highlights, extraction and characterization measures were consolidated into a solitary computerized framework. Crude EEG signal with no pre-processing is well-thought-out as contribution to the framework, further lessens the calculations. Four profound learning models have been proposed to extricate the most judicial highlights that upgrade the order exactness and expectation time. Our new approach exploits the convolutional neuronic organization in removing the huge spatial highlights from various scalp positions and the repetitive neural organization in expecting the frequency of ...