Paradoxical sleep stages detection using somnographic EOG signal for obese and no-obese patients
by S. Khemiri; K. Aloui; M.S. Naceur
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 8, No. 1/2, 2015

Abstract: The electroencephalographic (EEG) signal is crucial for the classification of sleep stages. Despite it is widely used for the analysis of sleep, several drawbacks were noted. If the EEG is contaminated by artefacts, no classification can be performed. In this context, we propose an alternative method based on using the electrooculographic (EOG) signal for automatic classification of paradoxical sleep stages. Our classification strategy is composed of three phases: a pre-processing phase to remove the different types of artefacts which contaminate the somnographic EOG signal, a descriptors extraction phase and an automatic detection of REM sleep stages phase. We tested our approach on the somnographic EOG signals from PHYSIOBANK database. Our experimental results present the interest of this method. In fact, we reached a total classification accuracy of 93.28% compared to expert's results that have used the four polysomnographic signals. Our classification results are related to BMI (Body Mass Index) of patients: when BMI augments the classification accuracy decrease.

Online publication date: Sun, 25-Jan-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com