基于脑电信号的驾驶疲劳预报关键参数选取  

The Choice of Driver Fatigue Prediction Key Parameters Based on EEG Recordings

作　　者：毛科俊[1] 刘小明[1] 赵晓华[1] 荣建[1] 

机构地区：[1]北京工业大学北京交通工程重点实验室,北京100124

出　　处：《北京工业大学学报》2010年第7期966-970,共5页Journal of Beijing University of Technology

基　　金：08科研基地-教委科技创新平台-驾驶失误机理及对策研究(JJ004011200803)

摘　　要：为了实现驾驶疲劳的及时预报,利用脑电仪在模拟驾驶中采集驾驶员的脑电数据.采用功率谱估计计算不同频段波能量分布情况,确定采用delta和alpha波实现驾驶疲劳预报是可行的.为此,采用BP神经网络构建预报系统,分别对delta波、alpha波单独输入和两者同时输入时预报精度进行验证,结果表明,两者同时输入时预报效果最理想,为车载实时驾驶疲劳预警系统开发提供依据.In order to get an early driving fatigue warning early,the EEG data for a driver was recorded by an EEG apparatus in a driving simulation environment.The power spectrum estimation was used to establish the power distribution with frequency bands.Delta and alpha activities were referred to be possible to predict driver fatigue early.So the prediction system was created by the BP neural network,the prediction performance was tested separately in three situations such as the delta activity input,the alpha activity input and the combination of both input.The result shows the prediction impact is the best when the input vector is the combination of both and has the basis on the development of driving fatigue warning system.

关 键 词：驾驶疲劳预报 脑电信号 功率谱 BP神经网络 

分 类 号：U491.31[交通运输工程—交通运输规划与管理]