Sleep Disorder Diagnosis using EEG based Deep Learning Techniques

Abstract

This Proposed system detects the sleep disorder through the EEG signals using by deep learning techniques (Alex net, Google net) in which EEG signals are used as inputs to a deep convolution network to solve visual recognition tasks. Electroencephalograph (EEG) based on sleep stage analysis is helpful for detect the sleep disorder. thirty-layer CNN model is designed to automatically detect the sleep disorder using EEG signals We Obtained accuracy to received output. Obtained good performance even with a smaller number of normal and sleep disorder data sets.