Feature extraction of human sleep EEG based on a peak frequency analysis

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.