Classical Sleep Stages and the Spectral Content of the Eeg Signal

Abstract

Polygraphic sleep recordings during 12 nights in 5 healthy [human] volunteers were classified manually into waking and the various sleep stages. The smoothed power spectra of EEG signal segments defined as waking or one of the sleep stages were calculated via segmentation of the EEG signal, using the autoregressive model, and time-dependent fuzzy clustering. The spectra were derived from the prediction coefficients of the segments. The relative power in the .delta. frequency band increased monotonically with increasing depth of sleep, together with a parallel decrease in the .alpha. relative power. In most cases, .alpha. relative power had a small peak during REM [rapid eye movement] sleep, and on average the relative power in the .sigma. frequency band during REM sleep was smaller than the .beta. relative power. The power spectra from subjects with no waking .alpha. differed from those of subjects with abundant waking .alpha. mostly in the relative spectral content of stages 1 and REM. These findings are discussed in relation to future standardization of automatic analysis of sleep recordings.