{"title":"低频心电信号生物特征识别方法的评价","authors":"A. Lyamin, Elena N. Cherepovskaya","doi":"10.1109/SAMI.2017.7880290","DOIUrl":null,"url":null,"abstract":"In order to provide high security level, different identification and verification methods are being used in information systems. A development of the new highly accurate methods are of great interest nowadays. Those methods that analyze biometric signals are becoming more widespread as biometric data can provide hardly forged information about a person. This paper presents the developed biometric identification approach and the results of its evaluation on the ECG data collected during the experimental study.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An evaluation of biometrie identification approach on low-frequency ECG signal\",\"authors\":\"A. Lyamin, Elena N. Cherepovskaya\",\"doi\":\"10.1109/SAMI.2017.7880290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to provide high security level, different identification and verification methods are being used in information systems. A development of the new highly accurate methods are of great interest nowadays. Those methods that analyze biometric signals are becoming more widespread as biometric data can provide hardly forged information about a person. This paper presents the developed biometric identification approach and the results of its evaluation on the ECG data collected during the experimental study.\",\"PeriodicalId\":105599,\"journal\":{\"name\":\"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2017.7880290\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2017.7880290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An evaluation of biometrie identification approach on low-frequency ECG signal
In order to provide high security level, different identification and verification methods are being used in information systems. A development of the new highly accurate methods are of great interest nowadays. Those methods that analyze biometric signals are becoming more widespread as biometric data can provide hardly forged information about a person. This paper presents the developed biometric identification approach and the results of its evaluation on the ECG data collected during the experimental study.