@article{ref1,
title="Estimating driving performance based on EEG spectrum analysis",
journal="EURASIP journal on advances in signal processing",
year="2005",
author="Lin, Chin-Teng and Wu, R. C. and Jung, Tzyy-Ping and Liang, Sheng-Fu and Huang, Tzu-Yi",
volume="2005",
number="19",
pages="3165-3174",
abstract="The growing number of traffic accidents in recent yearshas become a serious concern to society. Accidents caused bydriver's drowsiness behind the steering wheel have a high fatalityrate because of the marked decline in the driver's abilities ofperception, recognition, and vehicle control abilities whilesleepy. Preventing such accidents caused by drowsiness is highlydesirable but requires techniques for continuously detecting,estimating, and predicting the level of alertness of drivers anddelivering effective feedbacks to maintain their maximumperformance. This paper proposes an EEG-based drowsinessestimation system that combines electroencephalogram (EEG) logsubband power spectrum, correlation analysis, principal componentanalysis, and linear regression models to indirectly estimatedriver's drowsiness level in a virtual-reality-based drivingsimulator. Our results demonstrated that it is feasible toaccurately estimate quantitatively driving performance, expressedas deviation between the center of the vehicle and the center ofthe cruising lane, in a realistic driving simulator.<p />",
language="",
issn="1687-6172",
doi="10.1155/ASP.2005.3165",
url="http://dx.doi.org/10.1155/ASP.2005.3165"
}