Analysis of pilots' EEG map in take-off and landing tasks

被引:2
作者
Ji, Li [1 ,2 ,3 ]
Zhang, Chen [1 ]
Li, Haiwei [4 ]
Zhang, Ningning [5 ]
Zheng, Peng [3 ]
Guo, Changhao [1 ]
Zhang, Yong [6 ]
Tang, Xiaoyu [1 ]
机构
[1] Shenyang Aerosp Univ, Sch Mechatron Engn, Shenyang 110136, Peoples R China
[2] Brilliance Auto Grp Holdings Co Ltd, Automot Engn Res Inst, Shenyang, Peoples R China
[3] Shenyang Univ Technol, Sch Mech Engn, Shenyang, Peoples R China
[4] Shenyang Aircraft Corp, Shenyang, Peoples R China
[5] Shenyang Aerosp Univ, Sch Design & Art, Shenyang, Peoples R China
[6] Harbin Inst Technol, Harbin, Peoples R China
来源
BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK | 2022年 / 67卷 / 05期
关键词
beta-wave; EEG map; electroencephalogram (EEG); safe flight; take-off and landing; REAL-TIME ASSESSMENT;
D O I
10.1515/bmt-2021-0418
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The take-off and landing phases are considered the critical stages of aircraft flight. To ensure flight efficiency and safety in the critical stages, this research proposes a method for analyzing and monitoring pilot flight status by beta-wave. The focus of the study is beta potential changes on the EEG map. First, the proportion of beta-wave in the electroencephalogram (EEG) of pilots during take-off and landing increases significantly. Second, the EEG map accurately and intuitively reflects the spatial distribution of potential changes in brain regions. Finally, correlation and machine learning are used for further research of beta-wave. The conclusions show that the significant changes in the beta-wave caused by take-off and landing can be seen in the EEG map to identify and adjust the pilot's state. Therefore, this research provides more accurate and effective reference information (like the EEG map, correlation and machine learning) for efficient and safe flight training in the critical stages.
引用
收藏
页码:345 / 356
页数:12
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