%0 Journal Article
	%A Wei-Chih Tang and  Shih-Wei Lu and  Chih-Mong Tsai and  Cheng-Yan Kao and  Hsiu-Hui Lee
	%D 2007
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 9, 2007
	%T Harmonic Parameters with HHT and Wavelet Transform for Automatic Sleep Stages Scoring
	%U https://publications.waset.org/pdf/3865
	%V 9
	%X Previously, harmonic parameters (HPs) have been
selected as features extracted from EEG signals for automatic sleep
scoring. However, in previous studies, only one HP parameter was
used, which were directly extracted from the whole epoch of EEG
signal.
In this study, two different transformations were applied to extract
HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet
transform (WT). EEG signals are decomposed by the two
transformations; and features were extracted from different
components. Twelve parameters (four sets of HPs) were extracted.
Some of the parameters are highly diverse among different stages.
Afterward, HPs from two transformations were used to building a
rough sleep stages scoring model using the classifier SVM. The
performance of this model is about 78% using the features obtained by
our proposed extractions. Our results suggest that these features may
be useful for automatic sleep stages scoring.
	%P 2722 - 2725