Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG.
Analysis and classification of sleep stages is essential in sleep research. In this particular study, an alternative system which estimates sleep stages of human being through a multi-layer neural network (NN) that simultaneously employs EEG, EMG and EOG. The data were recorded through polisomnography device for 7 h for each subject. These collective variant data were first grouped by an expert physician and the software of polisomnography, and then used for training and testing the proposed Artificial Neural Network (ANN). A good scoring was attained through the trained ANN, so it may be put into use in clinics where lacks of specialist physicians.
Tagluk
M Emin
ME
Department of Electrical and Electronics Engineering, University of Inonu, Malatya, Turkey.
Sezgin
Necmettin
N
Akin
Mehmet
M
D004569:Electroencephalography; D004576:Electromyography; D004585:Electrooculography; D006801:Humans; D016571:Neural Networks, Computer; D017286:Polysomnography; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012894:Sleep Stages