{"title":"SU-PhysioDB: A physiological signals database for body area network security","authors":"Duygu Karaoglan, A. Levi, V. Tuzcu","doi":"10.1109/BlackSeaCom.2017.8277692","DOIUrl":null,"url":null,"abstract":"This paper presents a new physiological signals database, SU-PhysioDB, that contains simultaneous measurements of electrocardiogram (ECG), blood pressure (BP) and body temperature (BT) signals. SU-PhysioDB can be used to evaluate the performance of the security mechanisms designed for the communication among the biosensors within Body Area Networks (BANs). We present a detailed description of our SU-PhysioDB database along with providing a performance comparison of two specific physiological parameter generation techniques using a public database and our SU-PhysioDB da-tabase. Results show that our SU-PhysioDB database is a pros-pering option to be used while evaluating the performance of a bio-cryptographic security infrastructure designed for BANs.","PeriodicalId":126747,"journal":{"name":"2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BlackSeaCom.2017.8277692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents a new physiological signals database, SU-PhysioDB, that contains simultaneous measurements of electrocardiogram (ECG), blood pressure (BP) and body temperature (BT) signals. SU-PhysioDB can be used to evaluate the performance of the security mechanisms designed for the communication among the biosensors within Body Area Networks (BANs). We present a detailed description of our SU-PhysioDB database along with providing a performance comparison of two specific physiological parameter generation techniques using a public database and our SU-PhysioDB da-tabase. Results show that our SU-PhysioDB database is a pros-pering option to be used while evaluating the performance of a bio-cryptographic security infrastructure designed for BANs.