基于心电和脑电的驾驶疲劳检测研究

驾驶疲劳是引发交通事故的重要原因。驾驶疲劳检测不仅具有重要的理论研究价值,同时也将产生重大的社会、经济效益。该文通过心电信号计算驾驶过程中的不同阶段的心率和脑电信号,经过功率谱估计后,计算得到功率谱频段比值,作为疲劳检测的指标。模拟驾驶实验中,对驾驶前后两个阶段的19位被试者的生理指标作统计显著性检验,实验结果表明,该文提出的心电和脑电指标可以有效地对驾驶的疲劳和清醒状态进行检测。

ECG and EEG Based Detection of Driver Fatigue

Driver fatigue is an important factor in traffic accidents. Detection of driver fatigue not only has important theoretical significance,but also will have significant social and economic benefits. Through driving simulation,we collected ECG and EEG for 19 subjects. At the same time,the subjects were asked to fill out the subjective fatigue evaluation sheet as a reference. Heart rate at different stages of driving was calculated by ECG,while the power spectrum band ratio was calculated after EEG power spectrum estimation. They were used as indicators of fatigue detection. The physiological indicators of 19 subjects before and after driving, were taken for statistical significance test,the results of the experiment show that the ECG and EEG indicators can effectively detect driver fatigue and alert.