A Correlation-based Biometric Identification Technique for ECG, PPG and EMG

P. Faragó, R. Groza, Liliana Ivanciu, S. Hintea
{"title":"A Correlation-based Biometric Identification Technique for ECG, PPG and EMG","authors":"P. Faragó, R. Groza, Liliana Ivanciu, S. Hintea","doi":"10.1109/TSP.2019.8768810","DOIUrl":null,"url":null,"abstract":"With the increase in the number of nodes connected to a wireless body area network (WBAN), transmitting biomedical data with the purpose of continuous health monitoring, authentication is a key element to maintain confidentiality in an open environment. In this context, this paper investigates the employment of biometrics extracted from biomedical signals, namely electrocardiogram, photopletysmogram and electromyogram, monitored by the WBAN nodes for user identification. The proposed biometric feature extraction technique is based on cross-correlating the biomedical signal to a reference signal. As such, biometrics extraction is solved with a procedure similar to the morphological analysis of the biomedical signal. Simulation results prove the applicability of the proposed technique.","PeriodicalId":399087,"journal":{"name":"2019 42nd International Conference on Telecommunications and Signal Processing (TSP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 42nd International Conference on Telecommunications and Signal Processing (TSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSP.2019.8768810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

With the increase in the number of nodes connected to a wireless body area network (WBAN), transmitting biomedical data with the purpose of continuous health monitoring, authentication is a key element to maintain confidentiality in an open environment. In this context, this paper investigates the employment of biometrics extracted from biomedical signals, namely electrocardiogram, photopletysmogram and electromyogram, monitored by the WBAN nodes for user identification. The proposed biometric feature extraction technique is based on cross-correlating the biomedical signal to a reference signal. As such, biometrics extraction is solved with a procedure similar to the morphological analysis of the biomedical signal. Simulation results prove the applicability of the proposed technique.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于相关性的心电、PPG和肌电生物特征识别技术
随着连接到无线体域网络(WBAN)的节点数量的增加,以持续健康监测为目的传输生物医学数据,身份验证是在开放环境中保持机密性的关键因素。在此背景下,本文研究了利用WBAN节点监测的从生物医学信号中提取的生物特征,即心电图、光电图和肌电图,用于用户识别。提出的生物特征提取技术是基于生物医学信号与参考信号的交叉相关。因此,采用类似于生物医学信号的形态分析的程序来解决生物特征提取问题。仿真结果证明了该方法的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Enhancement of Beat Tracking in String Quartet Music Analysis Based on the Teager-Kaiser Energy Operator Smart Speaker: Suspicious Event Detection with Reverse Mode Speakers Supervised Learning in Multi-Agent Environments Using Inverse Point of View Evaluation of Layer 3 Multipath Solutions using Container Technologies Detecting Cluster Synchronization in Chaotic Dynamic Networks via Information Theoretic Measures
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1