NDLI: Examining the relevance with sleep stages of time domain features of EEG, EOG, and chin EMG signals

Content Provider	IEEE Xplore Digital Library
Author	Gunes, S. Polat, K. Dursun, M. Yosunkaya, S.
Copyright Year	2009
Description	Author affiliation: Elektrik-Elektronik Mühendisli¿i Bölümü, Selçuk Üniversitesi, Konya, Turkey (Gunes, S.; Polat, K.; Dursun, M.) \|\| Uyku Laboratuvar¿, Gö¿üs Hastal¿klar¿ Bölümü, Meram T¿p Fakültesi, Selçuk Üniversitesi, Konya, Turkey (Yosunkaya, S.)
Abstract	Sleep staging has an important role in determining sleep disorders such as sleepiness, human fatigue etc. Sleep staging is generally done according to Rechtschaffen and Kales standard (RKS) using EEG signal obtained from PSG signals taken from patient subjects who come with any sleep disorders. Sleep stages are generally divided into three stages including awake, REM and N-REM (stage 1, stage 2, and stage 3). In this study, time domain features of EEG, EOG of right and left eyes, and chin EMG signals belonging to sleep stages were investigated and correlation between these time domain features and sleep stages was calculated. The used time domain features are mean value, standard deviation, peak value, skewness, kurtosis, and shape factor belonging to EEG, EOG of right and left eyes, and chin EMG signals. In experimental studies, PSG recordings of 3 subjects were taken and average recording time of 6.22 h, total recording time was 18.67 h. When investigated correlation coefficients, it is seen that skewness feature in time domain features of EEG signal, standard deviation feature in time domain features of EOG signals belonging to right and left eyes, and mean value feature in time domain features of chin EMG signal were more correlated with sleep stages than other features. Consequently, a feature vector can be constituted combining features determined from time domain features of EEG, EOG belonging to right and left eyes, and chin EMG signals. This obtained feature vector can be easily used in distinguishing sleep stages.
Starting Page	1
Ending Page	4
File Size	506100
Page Count	4
File Format	PDF
ISBN	9781424436057
DOI	10.1109/BIYOMUT.2009.5130256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-20
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrooculography Sleep Eyes Shape Humans Fatigue Electroencephalography Electromyography
Content Type	Text
Resource Type	Article

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