基于脑电信号特征的驾驶疲劳检测方法研究

目前,疲劳驾驶已成为一种严重的社会问题,然而对于疲劳驾驶的检测与预防仍缺乏有效的技术手段.采用疲劳驾驶模拟实验、结合对象辨别实验和对被试面部表情变化分析,探索了脑电信号特征与驾驶疲劳状态间的相关性.提取脑电信号的δ波、θ波、α波、β波四种脑电节律的能量值作为疲劳驾驶的特征值,采用δ波能量值与θ波能量值之和与β波能量值的比值作为疲劳指数.结果显示,疲劳指数与被试疲劳程度呈正相关,验证了利用脑电信号检测疲劳程度的合理性与客观性,为疲劳检测提供了新的思路.

The Detection Method for Driving Fatigue Based on EEG Signals

Fatigue driving has become a serious social problem in recent years. However,there is still a lack of effec-tive technical measure for detecting and preventing the fatigue driving. The correlation between EEG signal characteris-tics and driving fatigue state was investigated by using a fatigue driving simulation experiment as well as an object dis-crimination experiment. The facial expression of subjects in the fatigue driving simulation experiment was recorded for analysis. The EEG energy of four rhythms of β,θ,α, and β waves were extracted. The ratio of δ + θ andβ EEG energy was used as the model of driving fatigue index. The results showed a strong positive correlation be-tween driving fatigue index and fatigue state,which verified the rationality and objectivity for fatigue detection by using EEG signals,and shed light on a new method for driving fatigue detection.