Automatic detection of slow wave sleep using two channel electro-oculography.

An automatic method was developed for detecting slow wave sleep (SWS). The automatic method is based on a two-channel electro-oculography (EOG) with left mastoid (M1) as reference. Synchronous electroencephalographic (EEG) activity was detected by calculating cross-correlation between the two EOG channels by using 0.5-6 Hz band. An amplitude criterion was used for detecting slow waves and beta power 18-30 Hz was used to exclude artefacts. The automatic scoring was compared to a standard visual sleep scoring based on EOG, central EEG and submental EMG. Sleep EEG and EOG were recorded from 265 subjects. The optimal cross-correlation, amplitude and beta thresholds were derived using data from 133 training subjects and then applied to the data from different 132 validation subjects. Results were most sensitive to the changes in the amplitude criteria. Cohen's Kappa between the visual and the new developed automatic scoring in separating non-SWS and SWS was substantial (0.70) with epoch-by-epoch agreement of 93%. SWS epoch detection sensitivity was 75% and specificity was 96%. Also the total amount of slow waves, slow wave time (SWT), was estimated. The advantage of the automatic method is that it could be applied during online recordings using only four disposable self-adhesive electrodes.