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Estimation of Sleep Stages by an Artificial Neural Network Employing

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dc.contributor.author Tagluk, ME
dc.contributor.author Sezgin, N
dc.contributor.author Akin, M
dc.date.accessioned 2022-03-28T12:20:37Z
dc.date.available 2022-03-28T12:20:37Z
dc.date.issued 2010
dc.identifier.uri http://hdl.handle.net/11616/58287
dc.description.abstract 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.
dc.source JOURNAL OF MEDICAL SYSTEMS
dc.title Estimation of Sleep Stages by an Artificial Neural Network Employing


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