EEG-Based Automatic Sleep Stage Classification
Sleep
Sleep Stages
DOI:
10.26717/bjstr.2018.07.001535
Publication Date:
2018-11-28T04:26:07Z
AUTHORS (1)
ABSTRACT
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.
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