The Measurement and Processing of EEG Signals to Evaluate Fatigue

Abstract

Fatigues and drowsiness influentially affect human minds ability and capability to proceed correctly. Human fatigue and drowsiness are a major cause of brain’s inefficiency and ineffectiveness. This phenomenon is of great Psycho-sociological concerns among scholars. Monitoring EEG signals provides the possibility of detecting the extreme fatigue conditions and warning of it in vital circumstances such as long way driving and monotonous exercises. The aim of this paper is to describe an EEG-based fatigue signal measurements and to report its trustworthiness. Methodology: Changes in all major EEG signals during alert and fatigue conditions were used to develop the algorithm for detecting different levels of fatigue in laboratory conditions on 17 subjects. Results: The MATLAB software was shown to be able of identifying fatigue with 83% accurately in 17 subjects undergone the tests. The percentage of time the subjects were detected to be in different stages of fatigue was moderately different than the alert phase. Discussion and debates: To our knowledge, this is the first measurement software described that has shown to detect fatigue based on EEG signal changes in different frequency bands. It seems that more field research is required to evaluate the fatigue software in order to produce a robust and reliable fatigue measurement system.