Article(id=1281608118140383248, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608117335068953, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.03.0442, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757347200000, receivedDateStr=2025-09-09, revisedDate=1764518400000, revisedDateStr=2025-12-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1783488786492, onlineDateStr=2026-07-08, pubDate=1774627200000, pubDateStr=2026-03-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783488786492, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783488786492, creator=13701087609, updateTime=1783488786492, updator=13701087609, issue=Issue{id=1281608117335068953, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='3', pageStart='1', pageEnd='270', issueExtLink='null', onlineDate='null', pubDate='1774627200000', pubDateStr='2026-03-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783488786300, creator='13701087609', updateTime=1783588670896, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027063758533259, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608117335068953, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027063758533260, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608117335068953, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=41, endPage=48, ext={EN=ArticleExt(id=1281608118320738321, articleId=1281608118140383248, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Pilot mental workload assessment based on single-electrode EEG signals, columnId=1277328386947150682, journalTitle=China Safety Science Journal, columnName=Safety Science Theories and Methods, runingTitle=null, highlight=null, articleAbstract=

In order to overcome the limitations of traditional multi-electrode electroencephalography technology in flight applications and effectively assess the mental workload of pilots, 43 pilots were recruited in this study to conduct simulated flight experiments. Each participant was required to perform flight tasks at three different mental workload levels (low, medium, and high) using a Cessna 172R simulator. The low workload task involved a standard five-leg takeoff and landing route, while the medium and high workload tasks were variations of the low workload task, with the addition of one and three malfunctions, respectively. Heart rate signals, EEG signals (collected from the Frontal Pole(FP) 1 electrode), and National Aeronautics and Space Administration-Task Load Index(NASA-TLX) scale data were recorded. The results show that as mental workload increased, both NASA-TLX scale scores and heart rate exhibited an upward trend. The power values in the Alpha and Beta bands significantly increased as mental workload levels increased. A threshold based on the percentage increase in EEG power was established. When the power increase exceeded the threshold, it was classified as medium or high mental workload, triggering an alert. The findings suggest that single-electrode EEG signals based on the FP1 electrode can effectively assess the mental workload levels of pilots.

, authors=Hao JIANG^{1, 2}, Chao ZHANG^{1, 2}, Xueying LUO^{1, 2}, Xing PENG^{1, 2}, authorsList=Hao JIANG, Chao ZHANG, Xueying LUO, Xing PENG, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281608118677254162, articleId=1281608118140383248, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于单电极脑电信号的飞行员脑力负荷评估, columnId=1277328387270112092, journalTitle=中国安全科学学报, columnName=安全科学理论与方法, runingTitle=null, highlight=null, articleAbstract=

为克服传统多电极脑电技术在飞行应用中的局限性，有效评估飞行员脑力负荷，招募43名飞行员进行模拟飞行试验，每名被试需在Cessna 172R模拟器上执行低、中、高3种脑力负荷水平的飞行任务；低负荷任务为常规五边起落航线任务，中、高负荷任务是在低负荷任务基础上分别增加1项和3项故障；采集被试的心率信号、脑电信号（EEG）（从左侧前额电极（FP1）采集）和美国航空航天局任务负荷指数（NASA-TLX）量表数据，FP1单电极脑电时域信号首先经滤波、分段、去除极值等预处理，然后经快速傅里叶变换转换为频域信号，最后提取各波段的功率。试验结果表明：随着脑力负荷的提升，NASA-TLX量表得分和心率呈现上升趋势，α波段和β波段功率值随着脑力负荷水平的提升而显著增加；进一步设定功率上升百分比阈值，当超过该阈值时，判定为中、高脑力负荷并触发预警。基于FP1通道的单电极EEG能够有效地评估飞行员的脑力负荷水平。

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²中国民用航空飞行学院 国产民机飞行与运行支持四川省工程研究中心，四川 广汉 618307, bio={"content":"

蒋浩（1985—），男，四川绵阳人，博士，副教授，主要从事航空安全、航空人为因素等方面的研究。E-mail: huban@zju.edu.cn。

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蒋浩（1985—），男，四川绵阳人，博士，副教授，主要从事航空安全、航空人为因素等方面的研究。E-mail: huban@zju.edu.cn。

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