心率变异性与驾驶疲劳相关性研究

Study of correlation between heart rate variability and driving fatigue

为获取与驾驶疲劳程度相关性较高的、可以量化的、客观的心电指标,对10名成年男性司机在驾驶仿真平台上进行心率变异性(HRV)检测与眼动跟踪同步实验研究.对HRV信号指标与评估疲劳的客观指标——PER-CLOSp80值进行相关性分析.结果表明,在HRV信号的线性指标中,表征交感-副交感神经张力平衡状态的频谱低频与高频部分比值与PERCLOSp80值的相关程度最大,皮尔逊相关系数达到0.728,可以作为实时监测驾驶疲劳的量化心电指标.为进一步解释HRV信号的混沌特性,采用非线性动力学方法进行R-R间期C0复杂度计算,该非线性指标与疲劳累积过程相关,可以用来衡量驾驶员在遇到应急危险状况下的控制能力.

Ten adult male drivers were tested on a driving simulation platform to find an objective,quantifiable electrocardiograph indicator which highly related with driving fatigue.Heart rate variability （HRV） signals were monitored and eye tracking was recorded simultaneously during the driving process.Then,the correlation between the indicators of HRV signals and the objective driving fatigue indicator-PERCLOS p80 was calculated.Results showed that,in the HRV frequency spectrum,the ratio of low to high frequency,which indicating the tension equilibrium of sympathetic and parasympathetic nervous system,had the maximum correlation with PERCLOS p80,and the Pearson＇s correlation coefficient was 0.728.So this ratio can be a real-time quantitative indicator for driving fatigue detection.For the HRV signals are chaotic,the R-R interval C_0 complexity is selected to represent the fatigue cumulating process.This non-linear indicator can be used to assess the driver＇s control and response ability when confronted with unexpected dangers.