DocumentCode :
3635844
Title :
Examining the effect of time and frequency domain features of EEG, EOG, and Chin EMG signals on sleep staging
Author :
Seral ?zşen;Salih G?neş;Şebnem Yosunkaya
Author_Institution :
Elektrik-Elektronik M?hendisligi B?l?m? Sel?uk ?niversitesi, Konya
fYear :
2010
fDate :
4/1/2010 12:00:00 AM
Firstpage :
1
Lastpage :
4
Abstract :
Sleep staging has an effective role in diagnosing sleep disorders. Sleep staging is generally done by a sleep expert through examining Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG) signals of the patients and determining the stages of sleep in different time sections. This type of sleep staging is preferred among the sleep experts but because it is rather tiring and time consuming task, attention to the automatic sleep staging systems has been begun to increase. In this study, we obtained EEG, EMG and EOG signals of five healthy people in Meram Faculty of medicine to use in sleep staging and extracted 74 features from them. We analyzed the effects of these features on sleep staging. We utilized from the sequential feature selection algorithm and Artificial Neural Networks in this application. We determined which features are more effective in classification of sleep stages and by this way we tried to guide researchers who will use EEG, EMG and EOG features in sleep staging. The highest classification accuracy was obtained as 69.30% with use of four features.
Keywords :
"Frequency domain analysis","Electroencephalography","Electrooculography","Electromyography","Sleep","Artificial neural networks","Medical diagnostic imaging","Feature extraction","Brain modeling"
Publisher :
ieee
Conference_Titel :
Biomedical Engineering Meeting (BIYOMUT), 2010 15th National
Print_ISBN :
978-1-4244-6380-0
Type :
conf
DOI :
10.1109/BIYOMUT.2010.5479867
Filename :
5479867
Link To Document :
بازگشت