Measuring Correlates of Mental Workload During Simulated Driving Using cEEGrid Electrodes: A Test–Retest Reliability Analysis

Stephan Getzmann, J. Reiser, Melanie Karthaus, G. Rudinger, E. Wascher
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引用次数: 5

Abstract

The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are associated with attention and the allocation of mental resources. EEG has also been used to study mental processes while driving, both in real environments and in virtual reality. However, conventional EEG methods are of limited use outside of controlled laboratory settings. While modern EEG technologies offer hardly any restrictions for the user, they often still have limitations in measurement reliability. We recently showed that low-density EEG methods using film-based round the ear electrodes (cEEGrids) are well-suited to map mental processes while driving a car in a driving simulator. In the present follow-up study, we explored aspects of ecological and internal validity of the cEEGrid measurements. We analyzed longitudinal data of 127 adults, who drove the same driving course in a virtual environment twice at intervals of 12–15 months while the EEG was recorded. Modulations in the alpha and theta frequency bands as well as within behavioral parameters (driving speed and steering wheel angular velocity) which were highly consistent over the two measurement time points were found to reflect the complexity of the driving task. At the intraindividual level, small to moderate (albeit significant) correlations were observed in about 2/3 of the participants, while other participants showed significant deviations between the two measurements. Thus, the test-retest reliability at the intra-individual level was rather low and challenges the value of the application for diagnostic purposes. However, across all participants the reliability and ecological validity of cEEGrid electrodes were satisfactory in the context of driving-related parameters.
使用cegrid电极测量模拟驾驶过程中精神负荷的相关因素:一项重测信度分析
脑电图反映心理过程,特别是与注意力和心理资源分配有关的α和θ频段的调制。脑电图也被用于研究驾驶时的心理过程,无论是在真实环境中还是在虚拟现实中。然而,传统的脑电图方法在受控实验室环境之外的应用有限。虽然现代脑电图技术对用户几乎没有任何限制,但它们在测量可靠性方面仍然存在局限性。我们最近表明,低密度脑电图方法使用基于薄膜的耳旁电极(ceeggrids),非常适合在驾驶模拟器中绘制驾驶汽车时的心理过程。在目前的后续研究中,我们探讨了cEEGrid测量的生态效度和内部效度。我们分析了127名成年人的纵向数据,他们在虚拟环境中驾驶相同的驾驶课程两次,间隔12-15个月,同时记录脑电图。在两个测量时间点上,α和θ频段以及行为参数(驾驶速度和方向盘角速度)的调制高度一致,反映了驾驶任务的复杂性。在个体水平上,在大约2/3的参与者中观察到小到中度(尽管显著)的相关性,而其他参与者在两种测量结果之间表现出显著的偏差。因此,在个体内部水平上的重测信度相当低,并挑战了应用于诊断目的的价值。然而,在所有参与者中,cEEGrid电极的可靠性和生态效度在驾驶相关参数的背景下是令人满意的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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