Wascher Edmund, Alyan Emad, Karthaus Melanie, Getzmann Stephan, Arnau Stefan, Reiser Julian Elias
IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany.
Heliyon. 2023 Jul 3;9(7):e17904. doi: 10.1016/j.heliyon.2023.e17904. eCollection 2023 Jul.
Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states.
驾驶安全很大程度上取决于驾驶员的心理状态以及对驾驶情况的注意力。先前的研究表明脑电图测量与心理状态之间存在明显关系，如警觉性和困倦，但通常只是对较长时间段内的心理状态进行映射。在这项驾驶模拟研究中，我们利用脑电图的高时间分辨率，以扫视、注视和眨眼等眼动形式捕捉眼动前后认知过程中的细粒度调制。共有15名受试者驾驶通过一条约50公里的路线，该路线包括高速公路、乡村道路和城市路段。根据大脑振荡阿尔法和西塔活动的比例，将总距离划分为10米长的低、中、高任务负荷路段。分析眨眼诱发和注视诱发的事件相关电位、频谱扰动和侧向化，作为认知和注意力的神经认知相关指标。根据基于脑电图的任务负荷估计，这些指标显示出与速度和转向加速度等驾驶行为参数相关的不同模式，并代表了驾驶过程中特定认知过程的高时间分辨率图像。在未来的应用中，这些脑电图测量的组合可以为驾驶员预警系统奠定基础，该系统通过考虑驾驶员注意力和心理状态的快速波动来提高整体驾驶安全性。
