Mind the road: attention related neuromarkers during automated and manual simulated driving captured with a new mobile EEG sensor system.

IF 1.5 Q3 ERGONOMICS
Frontiers in neuroergonomics Pub Date : 2025-03-12 eCollection Date: 2025-01-01 DOI:10.3389/fnrgo.2025.1542379
Joanna Elizabeth Mary Scanlon, Daniel Küppers, Anneke Büürma, Axel Heinrich Winneke
{"title":"Mind the road: attention related neuromarkers during automated and manual simulated driving captured with a new mobile EEG sensor system.","authors":"Joanna Elizabeth Mary Scanlon, Daniel Küppers, Anneke Büürma, Axel Heinrich Winneke","doi":"10.3389/fnrgo.2025.1542379","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Decline in vigilance due to fatigue is a common concern in traffic safety. Partially automated driving (PAD) systems can aid driving but decrease the driver's vigilance over time, due to reduced task engagement. Mobile EEG solutions can obtain neural information while operating a vehicle. The purpose of this study was to investigate how the behavior and brain activity associated with vigilance (i.e., alpha, beta and theta power) differs between PAD and manual driving, as well as changes over time, and how these effects can be detected using two different EEG systems.</p><p><strong>Methods: </strong>Twenty-eight participants performed two 1-h simulated driving tasks, while wearing both a standard 24 channel EEG cap and a newly developed, unobtrusive and easy to apply 10 channel mobile EEG sensor-grid system. One scenario required manual control of the vehicle (manual) while the other required only monitoring the vehicle (PAD). Additionally, lane deviation, percentage eye-closure (PERCLOS) and subjective ratings of workload, fatigue and stress were obtained.</p><p><strong>Results: </strong>Alpha, beta and theta power of the EEG as well as PERCLOS were higher in the PAD condition and increased over time in both conditions. The same spectral EEG effects were evident in both EEG systems. Lane deviation as an index of driving performance in the manual driving condition increased over time.</p><p><strong>Conclusion: </strong>These effects indicate significant increases in fatigue and vigilance decrement over time while driving, and overall higher levels of fatigue and vigilance decrement associated with PAD. The EEG measures revealed significant effects earlier than the behavioral measures, demonstrating that EEG might allow faster detection of decreased vigilance than behavioral driving measures. This new, mobile EEG-grid system could be used to evaluate and improve driver monitoring systems in the field or even be used in the future as additional sensor to inform drivers of critical changes in their level of vigilance. In addition to driving, further areas of application for this EEG-sensor grid are safety critical work environments where vigilance monitoring is pivotal.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1542379"},"PeriodicalIF":1.5000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937089/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in neuroergonomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fnrgo.2025.1542379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"ERGONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Decline in vigilance due to fatigue is a common concern in traffic safety. Partially automated driving (PAD) systems can aid driving but decrease the driver's vigilance over time, due to reduced task engagement. Mobile EEG solutions can obtain neural information while operating a vehicle. The purpose of this study was to investigate how the behavior and brain activity associated with vigilance (i.e., alpha, beta and theta power) differs between PAD and manual driving, as well as changes over time, and how these effects can be detected using two different EEG systems.

Methods: Twenty-eight participants performed two 1-h simulated driving tasks, while wearing both a standard 24 channel EEG cap and a newly developed, unobtrusive and easy to apply 10 channel mobile EEG sensor-grid system. One scenario required manual control of the vehicle (manual) while the other required only monitoring the vehicle (PAD). Additionally, lane deviation, percentage eye-closure (PERCLOS) and subjective ratings of workload, fatigue and stress were obtained.

Results: Alpha, beta and theta power of the EEG as well as PERCLOS were higher in the PAD condition and increased over time in both conditions. The same spectral EEG effects were evident in both EEG systems. Lane deviation as an index of driving performance in the manual driving condition increased over time.

Conclusion: These effects indicate significant increases in fatigue and vigilance decrement over time while driving, and overall higher levels of fatigue and vigilance decrement associated with PAD. The EEG measures revealed significant effects earlier than the behavioral measures, demonstrating that EEG might allow faster detection of decreased vigilance than behavioral driving measures. This new, mobile EEG-grid system could be used to evaluate and improve driver monitoring systems in the field or even be used in the future as additional sensor to inform drivers of critical changes in their level of vigilance. In addition to driving, further areas of application for this EEG-sensor grid are safety critical work environments where vigilance monitoring is pivotal.

注意道路:使用新的移动脑电图传感器系统捕获自动和手动模拟驾驶过程中与注意力相关的神经标记物。
背景:疲劳引起的警惕性下降是交通安全中普遍关注的问题。部分自动驾驶(PAD)系统可以辅助驾驶,但随着时间的推移,由于任务参与度降低,驾驶员的警惕性会降低。移动脑电图解决方案可以在驾驶车辆时获取神经信息。本研究的目的是调查PAD和手动驾驶之间与警觉性相关的行为和大脑活动(即α, β和θ功率)的差异,以及随时间的变化,以及如何使用两种不同的脑电图系统检测这些影响。方法:28名参与者在佩戴标准的24通道EEG帽和新开发的10通道移动EEG传感器网格系统的情况下,进行两个1小时的模拟驾驶任务。一种场景需要手动控制车辆(manual),而另一种场景只需要监视车辆(PAD)。此外,获得车道偏差、闭眼百分比(PERCLOS)和工作量、疲劳和压力的主观评分。结果:PAD组脑电图α、β、θ波功率及PERCLOS均较高,且随时间延长而升高。两种脑电系统均表现出相同的频谱脑电效应。车道偏差作为手动驾驶状态下的驾驶性能指标,随着时间的推移而增加。结论:这些影响表明,随着驾驶时间的推移,疲劳和警觉性下降显著增加,并且总体上较高水平的疲劳和警觉性下降与PAD相关。脑电图测量比行为测量更早地显示出显著的影响,表明脑电图可能比行为驾驶测量更快地检测到警觉性下降。这种新的移动脑电图网格系统可用于评估和改进现场驾驶员监控系统,甚至在未来用作额外的传感器,以通知驾驶员其警戒水平的关键变化。除了驾驶之外,这种脑电图传感器网格的进一步应用领域是对安全至关重要的工作环境,在这些环境中,警惕性监测至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信