EEG-Based Automatic Sleep Stage Classification

• DOI: 10.26717/bjstr.2018.07.001535
• Publication Date: 2018-11-28T04:26:07Z
• Authors: Nikolaos Giannakeas
• Keywords: Sleep; Sleep Stages

Sleep disorders have a great impact in the patients' quality of life.The study human sleep during different stages is crucial diagnosis and mainly performed with polysomnography (PSG).In this work, methodology for staging using solely Electroencephalographic (EEG) signals from PSG recordings presented.EEG ISRUC-Sleep dataset are selected used, aiming to automatically identify five stages.Initially, EEG signal filtered order extract rhythms energy calculated each sub-band used train several typical classifiers.Results terms classification accuracy reached 75.29% Random Forests.