基于EEG小波包子带能量比的疲劳驾驶检测方法

驾驶员在从正常驾驶状态向疲劳驾驶状态变化的过程中,其脑电信号中的慢波逐渐增加,快波逐渐减少;针对这一特点,提出了一种基于小波包子带能量比的疲劳驾驶状态检测方法.采集和分析受试者模拟驾驶过程中的脑电信号,利用小波包分解系数计算出β波与慢波的能量比,将其作为疲劳指标F值.实验结果表明,尽管不同受试者的F值存在较大差异,但是对于同一受试者而言,F值随着驾驶时间的延长和疲劳程度的增加而逐渐降低,其相对于正常驾驶状态的衰减程度能够有效反映驾驶人的疲劳程度.

A Fatigue Driving Detection Method Based on Wavelet Packet Sub-band Energy Ratio of EEG

As a driver's state varies from normal driving to fatigue driving, the slowly changing and the rapidly changing waves, which are in his/her EEG(electroencephalogram), increase and decrease gradually, respectively. So, it is possible to detect fatigue driving based on the energy ratio of wavelet packet sub-bands. The EEGs of some subjects were acquired and analyzed during their simulating driving. The energy ratio of β waves to slowly changing waves was computed from the decomposition coefficients of wavelet packets and it was defined as a fatigue index F. Experimental result shows that F value is dependent on subjects, and there are big difference among the subjects' F values. But for any subject, his/her F value decreases slowly with the increase of driving time and fatigue level. The attenuation level of F value compared with that of normal state can reflect the driver's fatigue level.