%0 Electronic Article %A David Pereira Coutinho %+ Instituto de Telecomunicações, 1049-001Lisboa, Portugal %+ Department of Electronics, Telecommunications and Computer Engineering, Instituto Superior de Engenharia de Lisboa, 1959-007Lisboa, Portugal %A Hugo Silva %+ Instituto de Telecomunicações, 1049-001Lisboa, Portugal %A Hugo Gamboa %+ Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516Caparica, Portugal %A Ana Fred %+ Instituto de Telecomunicações, 1049-001Lisboa, Portugal %+ Department of Electrical and Computer Engineering, Instituto Superior Técnico, 1049-001Lisboa, Portugal %A Mário Figueiredo %+ Instituto de Telecomunicações, 1049-001Lisboa, Portugal %+ Department of Electrical and Computer Engineering, Instituto Superior Técnico, 1049-001Lisboa, Portugal %K human identification %K robust signal acquisition devices %K performance evaluation %K computer activities %K ambulatory conditions %K healthy control individuals %K functional evaluation %K nonfiducial approach %K feature analysis methodologies %K electrophysiological sensing %K computer usage scenario %K ECG-based real-time biometric system %K classification methodologies %K cardiac electrophysiological assessment %K feature extraction %K data acquisition %K clinical-grade ECG recording %K noninvasive technique %K signal processing %K human authentication %K functional diagnostics %X The electrocardiogram (ECG) is a non-invasive and widely used technique for cardiac electrophysiological assessment. Although the ECG has traditionally only been used for functional diagnostic and evaluation, several advances in electrophysiological sensing have made available robust signal acquisition devices, particularly suited for ambulatory conditions, widening its range of applications. In particular, recent work has shown the potential of the ECG as a biometric trait, both for human identification and authentication. This study sets the ground for an ECG-based real-time biometric system. The authors describe an experimental setup and the evaluation of new fiducial and non-fiducial approaches, including data acquisition, signal processing, feature extraction and analysis and classification methodologies, showing the applicability of the ECG as a real-time biometric. Performance evaluation was done in clinical-grade ECG recording from 51 healthy control individuals (of a publicly available benchmark dataset) as well as on data collected from 26 healthy volunteers performing computer activities without any posture or motion limitations, thus simulating a regular computer usage scenario. %@ 2047-4938 %T Novel fiducial and non-fiducial approaches to electrocardiogram-based biometric systems %B IET Biometrics %D June 2013 %V 2 %N 2 %P 64-75 %I Institution of Engineering and Technology %U https://digital-library.theiet.org/;jsessionid=5132gpe86umot.x-iet-live-01content/journals/10.1049/iet-bmt.2012.0055 %G EN