4.1 Overview

The data analysis protocol is based on the following assumption:  In the time period that precedes severe performance degradation in vigilance related tasks, there are discernible changes in the subject's EEG waveform which can be detected using advanced signal processing methods.

Recall, the objective of this research investigation is:  To develop a signal processing methodology that can successfully differentiate between normal alertness and extreme sleepiness.  Extreme sleepiness refers to the state during which sleep is perceived as difficult to resist, the individual struggles against sleep, performance lapses occur, and sleep eventually ensues.

No detection system which can use the EEG waveform, which most experts agree would be the closest measure of the true state of consciousness of an individual, has been developed to date.  Furthermore, the signal processing techniques developed in this work, which can successfully differentiate between alertness and the initial stages of sleep, would greatly improve the state-of-the-art in EEG analysis for medical and diagnostic purposes.  The analysis of early sleep stages is critical in helping to identify many sleep disorders, including a very common complaint, the diagnosis of clinical insomnia.  And finally, continued research and technology development in various EEG related fields which build upon the research developed in this work cannot be underestimated.

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