Alert versus fatigue discriminator

Abstract

Described is a computer system for establishing an electroencephalogram (EEG) model for discriminating between alert and fatigue states. The computer system comprises a receiver module for receiving an alert state segment illustrative of an alert state of at least one subject, and one or more EEG fatigue data segments illustrative of a fatigue state of the at least one subject. The computer system further comprises a segment selector for selecting one of the one or more fatigue data segments and setting it to be an assumed maximum fatigue segment, an EEG classifier trainer for training an EEG classifier by extracting an EEG feature space from the alert state segment and assumed maximum fatigue segment, and a maximum fatigue identifier module for identifying a segment of maximum fatigue by applying the EEG classifier to each of the fatigue data segments. The computer system further comprises a segment comparator for determining if the segment of maximum fatigue is consistent with the assumed maximum fatigue segment, and a limit setter for setting the segment of maximum fatigue as a revised assumed maximum fatigue segment, if the segment of maximum fatigue is inconsistent with the assumed maximum fatigue segment, and supplying the EEG classifier trainer with the revised assumed maximum fatigue segment. The computer system further comprises a model output module for setting the EEG classifier as the EEG model for discriminating between alert and fatigue states in segments of EEG data, if the segment of maximum fatigue is consistent with the assumed maximum fatigue segment.