非侵入式和混合式驾驶员困倦检测系统开发的方法学和初步分析结果

E. Zilberg, D. Burton, Z. Xu, M. Karrar, Sara Lal
{"title":"非侵入式和混合式驾驶员困倦检测系统开发的方法学和初步分析结果","authors":"E. Zilberg, D. Burton, Z. Xu, M. Karrar, Sara Lal","doi":"10.1109/AUSWIRELESS.2007.44","DOIUrl":null,"url":null,"abstract":"Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals.","PeriodicalId":312921,"journal":{"name":"The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":"{\"title\":\"Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems\",\"authors\":\"E. Zilberg, D. Burton, Z. Xu, M. Karrar, Sara Lal\",\"doi\":\"10.1109/AUSWIRELESS.2007.44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals.\",\"PeriodicalId\":312921,\"journal\":{\"name\":\"The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless 2007)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"47\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUSWIRELESS.2007.44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUSWIRELESS.2007.44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47

摘要

提出将压电薄膜运动传感器集成到汽车座椅、安全带和方向盘中,开发一种非侵入式混合动力驾驶员睡意检测系统。设计了一项汽车模拟器研究来收集生理数据以验证该技术。提出了生理数据分析、驾驶员困倦独立评估以及通过序列拟合和回归模型选择开发困倦检测算法的方法。统计分析表明,在过渡到危险睡意水平的过程中,座椅传感器记录的运动变化正在减少。这一发现表明,压膜运动传感器可以作为一种非侵入性设备,用于检测自己或与其他生理信号相结合的困倦程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems
Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals.
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