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In order to explore the emotional expression characteristics of different types of groups under emergencies, and to deeply analyze the influence of gender, temperament type and accident environment on the stress state emotions of the groups, a stress state emotional stimulation test based on facial expression technology was designed. A cohort of 137 participants was exposed to five categories of accident videos. Facial expression data for six basic emotions were collected using FaceReader software, with the Kruskal-Wallis test employed to analyze differences across gender, temperament types, and accident scenarios. A k-means clustering model was further constructed based on arousal dynamic features. The results show that female participants exhibit significantly higher intensities of sadness and fear, whereas males show stronger anger responses. Sanguine individuals demonstrate the most pronounced emotional reactivity, while phlegmatic types achieve the fastest arousal modulation. Fear responses are most pronounced in building fire scenarios. Males outperform females in arousal self-regulation capacity.

, authors=Junqing MENG¹, Yunlian FU¹, Bin GAO², Jingyuan QIU¹, authorsList=Junqing MENG, Yunlian FU, Bin GAO, Jingyuan QIU, 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=1281627191825908049, articleId=1281627190999630157, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于面部表情识别的突发事故应激情绪反应差异, columnId=1277328338280645463, journalTitle=中国安全科学学报, columnName=公共安全与应急管理, runingTitle=null, highlight=null, articleAbstract=

为探究突发事件下不同类型群体情绪表达特征，深入分析性别、气质类型和事故环境对群体应激状态情绪的影响，基于面部表情技术设计应激状态情绪刺激试验。选取137名被试观看5类事故视频，采用Facereader软件采集6种基本情绪强度数据，通过非参数检验分析变量差异性，并构建基于唤醒度动态特征的k-means聚类模型。结果表明：女性悲伤与恐惧强度显著高于男性，而愤怒强度较低；多血质个体情绪反应最强烈，黏液质个体唤醒度调节速度最快；建筑火灾场景诱发的恐惧强度最显著；男性在应激状态下的唤醒度自我调节能力显著优于女性。

, authors=孟筠青副教授¹, 符运莲¹, 高滨², 邱敬渊¹, authorsList=孟筠青副教授, 符运莲, 高滨, 邱敬渊, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=l77i8jwX9H4NJKIRmz9upA==, magXml=Llisz+LqR2rPjTK3Tw7Q1Q==, pdfUrl=null, pdf=eBTpXrKXhSP4LIEaZPsVng==, pdfFileSize=6633841, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=cYAsq5bOgHa2jQBrN05FuA==, mapNumber=null, fund=null)}, authors=[Author(id=1281627192241144153, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190999630157, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=mengjunqing@cumtb.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281627192320835931, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190999630157, authorId=1281627192241144153, language=EN, stringName=Junqing MENG, firstName=Junqing, middleName=null, lastName=MENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹School of Emergency Management and Safety Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281627192396333404, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190999630157, authorId=1281627192241144153, language=CN, stringName=孟筠青副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹中国矿业大学（北京） 应急管理与安全工程学院，北京 100083, bio={"content":"

孟筠青（1981—），男，河北邢台人，博士，副教授，主要从事粉尘与职业危害防治、火灾防治、特种设备安全、安全心理、数值模拟及仿真等方面的研究。E-mail: mengjunqing@cumtb.edu.cn。

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孟筠青（1981—），男，河北邢台人，博士，副教授，主要从事粉尘与职业危害防治、火灾防治、特种设备安全、安全心理、数值模拟及仿真等方面的研究。E-mail: mengjunqing@cumtb.edu.cn。

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