A STATISTICAL OVERVIEW ON SLEEP SCORING

Abstract

t. In this study, sleep electroencephalography (EEG) which is frequentlyused in statistical modelling has been modelled with the autoregressive (AR) timeseries model and what kind of a structure the variance of the term white noiseincluded in the model represented in different sleep stages has been observed.Taking all of the stages scored in accordance with Rechtschaffen and Kales criterioninto account separately, epoches in each stage have been modelled with the AR andthe variance of the term white noise in this model has been monitored. The studyhas evaluated the sleep EEG variances of a subject. In accordance with the results,the heterogeneity at Stage 2 was thought to be the reason why the objectivedifferences appeared in scoring. It is thought that this data pointed out a necessitythat the period in Rechtschaffen and Kales scoring which is called Stage 2 must berevised.