Borghini G, Vecchiato G, Toppi J, Astolfi L, Maglione A, Isabella R, Caltagirone C, Kong W, Wei D, Zhou Z, Polidori L, Vitiello S, Babiloni F
IRCCS Fondazione Santa Lucia, via Ardeatina 306, Rome, Italy.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:6442-5. doi: 10.1109/EMBC.2012.6347469.
Driving tasks are vulnerable to the effects of sleep deprivation and mental fatigue, diminishing driver's ability to respond effectively to unusual or emergent situations. Physiological and brain activity analysis could help to understand how to provide useful feedback and alert signals to the drivers for avoiding car accidents. In this study we analyze the insurgence of mental fatigue or drowsiness during car driving in a simulated environment by using high resolution EEG techniques as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). Results suggest that it is possible to introduce a EEG-based cerebral workload index that it is sensitive to the mental efforts of the driver during drive tasks of different levels of difficulty. Workload index was based on the estimation of increase of EEG power spectra in the theta band over prefrontal areas and the simultaneous decrease of EEG power spectra over parietal areas in alpha band during difficult drive conditions. Such index could be used in a future to assess on-line the mental state of the driver during the drive task.
驾驶任务容易受到睡眠剥夺和精神疲劳的影响,会削弱驾驶员有效应对异常或紧急情况的能力。生理和大脑活动分析有助于了解如何向驾驶员提供有用的反馈和警报信号,以避免交通事故。在本研究中,我们通过使用高分辨率脑电图技术以及诸如心率(HR)和眨眼率(EBR)等神经生理变量,分析了在模拟环境中驾驶汽车时精神疲劳或困倦的发生情况。结果表明,有可能引入一种基于脑电图的大脑工作负荷指数,该指数对驾驶员在不同难度驾驶任务期间的精神努力敏感。工作负荷指数基于在困难驾驶条件下前额叶区域θ波段脑电图功率谱增加以及顶叶区域α波段脑电图功率谱同时降低的估计。这样的指数未来可用于在线评估驾驶员在驾驶任务期间的精神状态。