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基于脑电信号观察地下汽车驾驶员的认知反应

Cognitive Response of Underground Car Driver Observed by Brain EEG Signals.

作者信息

Zhang Yizhe, Guo Lunfeng, You Xiusong, Miao Bing, Li Yunwang

机构信息

School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.

Key Laboratory of Intelligent Mining Robotics, Ministry of Emergency Management, Beijing 100083, China.

出版信息

Sensors (Basel). 2024 Dec 4;24(23):7763. doi: 10.3390/s24237763.

Abstract

In auxiliary transportation within mines, accurately assessing the cognitive and response states of drivers is vital for ensuring safety and operational efficiency. This study investigates the effects of various vehicle interaction stimuli on the electroencephalography (EEG) signals of mine transport vehicle drivers, analyzing the cognitive and response states of drivers under different conditions to evaluate their impact on safety performance. Through experimental design, we simulate multiple scenarios encountered in real operations, including interactions with dynamic and static vehicles, personnel, and warning signs. EEG technology records brain signals during these scenarios, and data analysis reveals changes in the cognitive states and responses of drivers to different stimuli. The results indicate significant variations in EEG signals with interactions involving dynamic and static vehicles, personnel, and warning signs, reflecting shifts in the cognitive and response states of drivers. Additionally, the study examines the overall impact of different interaction objects and environments. The detailed analysis of EEG signals in different scenarios sheds light on changes in perception, attention, and responses related to drivers, which is critical for advancing safety and sustainability in mining operations.

摘要

在矿山辅助运输中,准确评估驾驶员的认知和反应状态对于确保安全和运营效率至关重要。本研究调查了各种车辆交互刺激对矿山运输车辆驾驶员脑电图(EEG)信号的影响,分析不同条件下驾驶员的认知和反应状态,以评估其对安全性能的影响。通过实验设计,我们模拟了实际操作中遇到的多种场景,包括与动态和静态车辆、人员以及警告标志的交互。EEG技术记录这些场景中的脑信号,数据分析揭示了驾驶员对不同刺激的认知状态和反应的变化。结果表明,在涉及动态和静态车辆、人员以及警告标志的交互中,EEG信号存在显著差异,反映了驾驶员认知和反应状态的变化。此外,该研究考察了不同交互对象和环境的总体影响。对不同场景中EEG信号的详细分析揭示了与驾驶员相关的感知、注意力和反应的变化,这对于推进采矿作业的安全和可持续性至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cbb5/11644968/6797d09e13a5/sensors-24-07763-g001.jpg

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