An Involuntary Single Channel EEG Signals Sleep Stage Detection, Classification and Analysis

Abstract

Sleep stage detection and further accurate classification is an important step for diagnosing the different sleep related diseases. In this research paper an effective method for automatic sleep stages detection from single channel EEG signal is presented. In this present work the various stages as Awake, first, second, third and fourth sleep stages and rapid eye movement are classified by using Empirical Mode Decomposition (EMD), Chi-square and Adaboost algorithm. This classification is based on some selected attributes. The accuracy of classifier for five stage and 6 stage is obtained as 92.14% and 90.77% respectively. Keyword : EEG, EMD, sleep stages, Chi-square, Hjorth parameter.