利用光电成像技术对情绪应激和生理应激进行分类

Kan Hong
{"title":"利用光电成像技术对情绪应激和生理应激进行分类","authors":"Kan Hong","doi":"10.1109/INSAI56792.2022.00027","DOIUrl":null,"url":null,"abstract":"Emotional stress status is normally to be intertwined with physical stress information. It is meaningful to classify stress for real application such as homeland security and health. In this study, the classification algorithms are proposed based on electro-optical imaging system, such as thermal imaging (TI) system and multispectral imaging (MSI) system. Through the proposed model, the classification signals of ES and PS are successfully obtained. Experiments show that the classification result is encouraging, and the accuracy of the proposed algorithm is over 90%. This study can lead to a useful system for the stress classification and real applications. This research can lay a foundation for the application of stress recognition.","PeriodicalId":318264,"journal":{"name":"2022 2nd International Conference on Networking Systems of AI (INSAI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of Emotional Stress and Physical Stress Using Electro-Optical Imaging Technology\",\"authors\":\"Kan Hong\",\"doi\":\"10.1109/INSAI56792.2022.00027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emotional stress status is normally to be intertwined with physical stress information. It is meaningful to classify stress for real application such as homeland security and health. In this study, the classification algorithms are proposed based on electro-optical imaging system, such as thermal imaging (TI) system and multispectral imaging (MSI) system. Through the proposed model, the classification signals of ES and PS are successfully obtained. Experiments show that the classification result is encouraging, and the accuracy of the proposed algorithm is over 90%. This study can lead to a useful system for the stress classification and real applications. This research can lay a foundation for the application of stress recognition.\",\"PeriodicalId\":318264,\"journal\":{\"name\":\"2022 2nd International Conference on Networking Systems of AI (INSAI)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Networking Systems of AI (INSAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INSAI56792.2022.00027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Networking Systems of AI (INSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INSAI56792.2022.00027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

情绪压力状态通常与身体压力信息交织在一起。压力分类对于国土安全、卫生等实际应用具有重要意义。本研究提出了基于光电成像系统的分类算法,如热成像(TI)系统和多光谱成像(MSI)系统。通过该模型,成功地获得了ES和PS的分类信号。实验表明,该算法的分类结果令人鼓舞,准确率达到90%以上。该研究可为应力分类和实际应用提供一个有用的系统。本研究可为应力识别的应用奠定基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Emotional Stress and Physical Stress Using Electro-Optical Imaging Technology
Emotional stress status is normally to be intertwined with physical stress information. It is meaningful to classify stress for real application such as homeland security and health. In this study, the classification algorithms are proposed based on electro-optical imaging system, such as thermal imaging (TI) system and multispectral imaging (MSI) system. Through the proposed model, the classification signals of ES and PS are successfully obtained. Experiments show that the classification result is encouraging, and the accuracy of the proposed algorithm is over 90%. This study can lead to a useful system for the stress classification and real applications. This research can lay a foundation for the application of stress recognition.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信