Review of algorithms for predicting fatigue using EEG

arXiv:2402.09443v1 Announce Type: cross
Abstract: Fatigue detection is of paramount importance in enhancing safety, productivity, and well-being across diverse domains, including transportation, healthcare, and industry. This scientific paper presents a comprehensive investigation into the application of machine learning algorithms for the detection of physiological fatigue using Electroencephalogram (EEG) signals. The primary objective of this study was to assess the efficacy of various algorithms in predicting an individual's level of fatigue based on EEG data.

abstract algorithms application arxiv cs.ai cs.lg detection diverse domains eeg eess.sp healthcare importance industry investigation machine machine learning machine learning algorithms paper productivity review safety transportation type