{"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.