Abstract: The bispectrum was used to analyze the electroencephalography (EEG) of drivers in the process of driving based on the fact that bispectrum is suitable for the signals of EEG that possess non-Gaussian and nonlinear properties. The two-hour signals were divided into six sections at a certain time interval, which were analyzed by using the AutoRegressive （AR） parameter model method to estimate bispectrum. The results show the bispectrum of EEG are very different at different times, so bispectrum can be used for the detection of driving fatigue.

Key words: EEG, bispectrum, driving fatigue, fatigue time, fatigue characteristics

摘要： 基于脑电信号的非高斯、非线性特性，采用非常有效的双谱分析方法来分析驾驶过程中的脑电信号。首先将驾驶2小时的脑电数据按一定的时间间隔分为6段，然后利用自回归（AR）模型双谱分析方法分析这些信号，研究不同时刻这些信号双谱结构的变化。分析结果显示，驾驶不同时刻的脑电双谱结构有很大差异，表明双谱分析方法有望成为驾驶疲劳检测的一个指标。

关键词: 脑电, 双谱, 驾驶疲劳, 疲劳时间, 疲劳特性