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Eyelid movements measured by Nightcap predict slow eye movements during quiet wakefulness in humans

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SummaryA precipitous decline in eyelid movements (ELMs) has been shown to be a highly reliable indicator of sleep onset. While ELMs correlate well with eye movements during waking and rapid eye movement (REM) sleep, the eye sensor remains silent during the period of slow eye movements (SEMs) typical of sleep onset. If the ELM density (e.g. ELMs per minute) dropped simultaneously with the appearance of SEMs prior to sleep onset, it could be a promising tool for identifying decreases in alertness prior to overt sleep onset. The present study was designed to determine whether the presence of SEMs in the transitional period preceding stage 1 sleep is reflected in decreases in ELM density. ELM densities were computed for 2.5‐s epochs with and without SEMs, as well as for 15‐s epochs. Decreases in ELM density not only were an excellent correlate of the appearance of SEMs during wakefulness with closed eyes, but also a good predictor of their occurrence (c. 82% accuracy) at a time resolution of 2.5 s. Based on these results, we conclude that ELM density reliably predicts moderate changes in the level of alertness during quiet wakefulness.
Title: Eyelid movements measured by Nightcap predict slow eye movements during quiet wakefulness in humans
Description:
SummaryA precipitous decline in eyelid movements (ELMs) has been shown to be a highly reliable indicator of sleep onset.
While ELMs correlate well with eye movements during waking and rapid eye movement (REM) sleep, the eye sensor remains silent during the period of slow eye movements (SEMs) typical of sleep onset.
If the ELM density (e.
g.
ELMs per minute) dropped simultaneously with the appearance of SEMs prior to sleep onset, it could be a promising tool for identifying decreases in alertness prior to overt sleep onset.
The present study was designed to determine whether the presence of SEMs in the transitional period preceding stage 1 sleep is reflected in decreases in ELM density.
ELM densities were computed for 2.
5‐s epochs with and without SEMs, as well as for 15‐s epochs.
Decreases in ELM density not only were an excellent correlate of the appearance of SEMs during wakefulness with closed eyes, but also a good predictor of their occurrence (c.
82% accuracy) at a time resolution of 2.
5 s.
Based on these results, we conclude that ELM density reliably predicts moderate changes in the level of alertness during quiet wakefulness.

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