Feature Extraction of Human Sleep EEG based on a Peak Frequency Analysis
| Authors: | Inoue Katsuhiro, Kyushu Institute of Technology, Japan
Tsujihata Tomohiro, Kyushu Institute of Technology, Japan
Kumamaru Kousuke, Kyushu Institute of Technology, Japan
Matsuoka Shigeaki, School of Medicine, University of Occupational and Environmental Health, Japan |
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| Topic: | 1.1 Modelling, Identification & Signal Processing |
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| Session: | Image Processing and Biomedical Applications |
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| Keywords: | Wavelet analysis, Electroencephalogram, sleep stages, signal processing, feature extraction. |
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Abstract
We have developed so far the automatic discrimination system of human sleep EEG stages based on a wave-shape recognition method. These systems were able to detect discrete stages (Stage MT, W, 1, 2, 3, 4, REM). But, more detailed information extraction was impossible by them. Therefore, in this paper, continuous wavelet analysis is applied to EEG signals in order to extract more precise information for the stages. A modified wavelet transform method is proposed and an extraction method of time series of peak frequency based on time-frequency analysis is introduced. And it is confirmed that our method is effective through the experimental studies.
