Abstract
Objective assessment of the sleep-wake states in clinical and laboratory settings is determined from the electroencephalogram (EEG) as recordings of brain electrical signals. The EEG record is visually scored according to the awake state and 4 stages of varying sleep depth, as well as a “rapid eye movement” (REM) or the dream stage. Drowsiness or the state between awake and sleep is not considered in this standard EEG scoring. Awareness of drowsiness is critical for individuals such as commercial truck drivers, pilots, railroad engineers and nuclear plant operators who are charged with maintaining high alertness in the performance of work that impacts public safety. Prevention of drowsiness progression to the sleep state once detected in these individuals is essential to avoid potential catastrophic events. The omission to include characterization of a drowsiness state was the impetus for a systematic investigation of high frequency EEG as potential marker for this purpose.
Recordings of EEG from study volunteers while performing various cognitive tasks and the sleep latency test were collected at the high sampling rate of 1000 Hz instead of the conventional 256 Hz. Discrete Fourier Transform of the time domain EEG to the frequency domain yielded 500 spectral components. From these components, a 1–15 Hz low frequency band (LFEEG) and a 201–500 Hz high frequency band (HFEEG) were extracted for comparison of relative energy proportion during each testing session.
In the sleep deprived condition, cognitive performance of the volunteers falters and concomitantly, the LFEEG energy proportion increases relative to the HFEEG. Tracking the EEG on a second-by-second basis in synchrony with the performance output provides a means for determining incipient drowsiness when responses to task stimuli are either prolonged or missing. Individual variability is markedly expressed in the examples given here of 2 volunteers: one resilient and one not resilient to the effects of sleep deprivation.
An Index of Alertness/Drowsiness and Cognitive Capacity has been developed based on quantitative comparison of the HFEEG and LFEEG spectral components and is currently in the patent application phase. Integration of this Index in an ambulatory EEG monitoring system will not only provide real time assessment of alertness and cognitive state but also permit emission of an audio or other warning signals if drowsiness is detected. This has application in the military as well as in the public safety arena for monitoring personnel in critical occupations requiring constant alertness over 24 hrs or longer.
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Sing, H.C. (2008). High Frequency EEG and Its Relationship to Cognitive Function. In: Lloyd, D., Rossi, E.L. (eds) Ultradian Rhythms from Molecules to Mind. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8352-5_14
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