Automatic detection of slow-wave sleep and REM-sleep stages using polysomnographic ECG signals

We describe in this paper a new approach of classifying the different sleep stages only by focusing on the polysomnographic ECG signals. We show the pre-processing technique of the ECG signals. At the same time the identification and elimination of the different types of artifacts which contain the signal and its reconstruction are shown. The automatic classification of the slow-deep sleep and the rapid eye movement sleep called in this work REM-sleep consists in extracting physiological indicators that characterize these two sleep stages through the polysomnographic ECG signal. In other words, this classification is based on the analysis of the cardiac rhythm during a night's sleep.