Cognitive Response of Underground Car Driver Observed by Brain EEG Signals
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 transpor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/23/7763 |
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| author | Yizhe Zhang Lunfeng Guo Xiusong You Bing Miao Yunwang Li |
| author_facet | Yizhe Zhang Lunfeng Guo Xiusong You Bing Miao Yunwang Li |
| author_sort | Yizhe Zhang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e0b4077faecb451eb4f0e54cc6d0b73e |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-e0b4077faecb451eb4f0e54cc6d0b73e2025-08-20T02:50:37ZengMDPI AGSensors1424-82202024-12-012423776310.3390/s24237763Cognitive Response of Underground Car Driver Observed by Brain EEG SignalsYizhe Zhang0Lunfeng Guo1Xiusong You2Bing Miao3Yunwang Li4School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaIn 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.https://www.mdpi.com/1424-8220/24/23/7763coal minemine transport vehicledriver cognitionEEGsignal processing |
| spellingShingle | Yizhe Zhang Lunfeng Guo Xiusong You Bing Miao Yunwang Li Cognitive Response of Underground Car Driver Observed by Brain EEG Signals Sensors coal mine mine transport vehicle driver cognition EEG signal processing |
| title | Cognitive Response of Underground Car Driver Observed by Brain EEG Signals |
| title_full | Cognitive Response of Underground Car Driver Observed by Brain EEG Signals |
| title_fullStr | Cognitive Response of Underground Car Driver Observed by Brain EEG Signals |
| title_full_unstemmed | Cognitive Response of Underground Car Driver Observed by Brain EEG Signals |
| title_short | Cognitive Response of Underground Car Driver Observed by Brain EEG Signals |
| title_sort | cognitive response of underground car driver observed by brain eeg signals |
| topic | coal mine mine transport vehicle driver cognition EEG signal processing |
| url | https://www.mdpi.com/1424-8220/24/23/7763 |
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