7.1  Summary/re-cap of research objectives

The purpose of this research was to develop signal processing methods to detect and track subtle changes in the signal characteristics of the EEG that precede performance lapses and the onset of sleep.  This required defining measures that were indicative of a reduced state of alertness in an individual and then developing advanced signal processing methods that extract this information from the EEG data.  Individuals could then be warned if their physiologic measures indicate a dangerously low state of alertness.  Of course, the value of the physiologic measure that corresponds to a dangerous state is application specific.  Also, because we are detecting the decreases in alertness and vigilance that precede the onset of sleep, an individual can be given sufficient warning time to react accordingly and take steps to avoid impending sleep.

The research goal for this project was:  To create a signal processing methodology for processing a single channel of EEG data such that an automated system can successfully differentiate between normal alertness and extreme sleepiness.  Here, 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.

This goal provided both the motivation and the basis for the research conducted as described in this document.  This document has established that:  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.

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