Application of music in relief of driving fatigue based on EEG signals

Abstract

In order to solve the problem of traffic accidents caused by fatigue driving, the research of EEG signals is particularly important, which can timely and accurately determine the fatigue state and take corresponding measures. Effective fatigue improvement measures are an important research topic in the current scientific field. The purpose of this article is to use EEG signals to analyze fatigue driving and prevent the dangers and injuries caused by fatigue driving. We designed the electroencephalogram (EEG) signal acquisition model to collect the EEG signal of the experimenter, and then removed the noise through the algorithm of Variational Mode Decomposition (VMD) and independent component analysis (ICA). On the basis of in-depth analysis and full understanding, we learned about the EEG signal of the driver at different driving times and different landscape roads, and provided some references for the study of music in relieving driving fatigue. The results of the study show that in the presence of music, the driver can keep the EEG signal active for more than 2\xa0h, while in the absence of music, the driver’s EEG signal is active for about 1.5\xa0h. Under different road conditions, the driver’s EEG signal activity is not consistent. The β wave and ( α \u2009+\u2009 θ )/ β ratio of the driver in mountainous roads and grassland road landscape environments are highly correlated with driving time, and β wave is negatively correlated with driving time, and ( α \u2009+\u2009 θ )/ β is positively correlated with driving time. In addition, the accumulation of changes in the two indicators is also strongly correlated with driving time.