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    • Two experienced sleep scorers one board certified evaluated

    2018-10-26

    Two experienced sleep scorers (one board certified) evaluated seven hours of recording. The recording contained 6h and 45min of sleep preceded by 15min of wakefulness. Both scorers analysed first the standard EEG cantharidin then repeated the process looking exclusively at the intra-ear and inter-ear channels and EOG. Each 30s period was scored as either wake, N1, N2, N3 or REM. If the scores in an epoch differed it was jointly rescored and consensus reached (less than 10% of periods). Scalp referenced EEG (ERI-M1) was not evaluated to avoid mixing the two types of EEG signal. Submentalis EMG was lost due to electrode failure. Scorers followed AASM criteria for sleep scoring [5]. This requires an amplitude above 75 µV in stage N3. Since signals had to be magnified by a cantharidin factor of 5 in order to appear similar this cut-off was reduced to 15µV in the ear-EEG. The resulting hypnograms for standard and ear EEG were compared.
    Results Visual comparison of short EEG epochs revealed striking similarities (Fig. 2). The ear-EEG amplitudes are reduced compared to the scalp channels, but the individual waveforms can be identified and appear similar between scalp and ear EEG channels. To ease the visual comparison of signals we displayed ear-EEG with increased sensitivity. Sensitivity adjustments in the intra-ear channel make the use of low-cut filters at 2Hz necessary in order to keep some parts of the record visually interpretable. Panel B shows a K-complex. In panel C a sleep spindle is observed. Whereas the K-complex is less distinct in the ear-EEG channels than in standard EEG, the rapid oscillating morphology of the sleep spindle is fairly distinct in the intra-ear channel. Spectral density estimates of the signals (Fig. 3) in two different states: wakefulness with closed eyes (75s) and slow wave sleep (75s). The graphs follow a similar trajectory being vertically displaced versions of each other reflecting the decreasing signal amplitudes with increasing proximity of the active electrode to the reference. In both states, the peak frequencies approximately align across the four channels. The two different hypnograms are plotted for comparison (Fig. 4). There is exact agreement between timing of sleep onset. The scores of N1, N2 and N3 are similar and for wakefulness and REM the scores are almost identical between EEG types. Of the total 846 scored epochs there is agreement in 90.9% between ear-EEG and standard EEG. In the standard EEG 30.5% of sleep time is spent in N3 sleep compared to 24.7% when evaluated from ear-EEG. For N2 the percentages are 40% and 45.3%, respectively. This suggests that ear-EEG slightly underestimates N3 and overestimates N2. REM onset and time spent in REM sleep was found to be the same in both standard and ear-EEG, but REM sleep staging was only possible by including assessment of EOG channels. In most cases of discrepancy between staging based on ear EEG is to mistaking N3 for N2, whereas the timing of wakefulness and REM is very similar. Less than 2% of the recording is spent in N1 sleep which is too little to determine significant deviances of using either method.
    Discussion Sleep staging results were highly similar between scalp EEG and ear-EEG. REM sleep staging with ear-EEG necessitates at least use of EOG channels, which also accounts for the high agreement for REM between the two methods. Ear EEG slightly overestimates the amount of N2 and underestimates time spent in N3 sleep. One possible explanation for this could be the partial reliance of low cut filters at 2Hz which eliminate very slow wave sleep characteristics. The 2Hz low cut was used whenever amplified low frequency noise resulted from the sensitivity adjustment rendered the 0.5Hz low cut channel too obscured for visual analysis. Time spent in N1 sleep was less than 2% of the entire record and is too little to determine if abiogenesis can be reliably staged by ear-EEG or not. Given the overall similarity between hypnograms derived from standard and ear-EEG it seems plausible that ear-EEG sleep staging is possible, but further testing is required before any generalisations of the method can be stated given inter-individual and age-related differences. A better approach to the problem of noise frequency noise interfering with visual analysis is also desirable.