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Evolution, current challenges, and future possibilities in ECG biometrics

dc.contributor.authorPinto, João Ribeiro
dc.contributor.authorCardoso, Jaime S.
dc.contributor.authorLourenço, André Ribeiro
dc.date.accessioned2018-12-07T11:07:42Z
dc.date.available2018-12-07T11:07:42Z
dc.date.issued2018
dc.description.abstractFace and fingerprint are, currently, the most thoroughly explored biometric traits, promising reliable recognition in diverse applications. Commercial products using these traits for biometric identification or authentication are increasingly widespread, from smartphones to border control. However, increasingly smart techniques to counterfeit such traits raise the need for traits that are less vulnerable to stealthy trait measurement or spoofing attacks. This has sparked interest on the electrocardiogram (ECG), most commonly associated with medical diagnosis, whose hidden nature and inherent liveness information make it highly resistant to attacks. In the last years, the topic of ECG-based biometrics has quickly evolved toward the commercial applications, mainly by addressing the reduced acceptability and comfort by proposing new off-the-person, wearable, and seamless acquisition settings. Furthermore, researchers have recently started to address the issues of spoofing prevention and data security in ECG biometrics, as well as the potential of deep learning methodologies to enhance the recognition accuracy and robustness. In this paper, we conduct a deep review and discussion of 93 state-of-the-art publications on their proposed methods, signal datasets, and publicly available ECG collections. The extracted knowledge is used to present the fundamentals and the evolution of ECG biometrics, describe the current state of the art, and draw conclusions on prior art approaches and current challenges. With this paper, we aim to delve into the current opportunities as well as inspire and guide future research in ECG biometrics.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPINTO, João Ribeiro; CARDOSO, Jaime S.; LOURENÇO, André Ribeiro – Evolution, current challenges, and future possibilities in ECG biometrics. IEEE Access. ISSN 2169-3536. Vol. 6, (2018), pp. 34747-34776pt_PT
dc.identifier.doi10.1109/ACCESS.2018.2849870pt_PT
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/10400.21/9142
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8392675pt_PT
dc.subjectBiosensorspt_PT
dc.subjectElectrocardiographypt_PT
dc.subjectBiossensorespt_PT
dc.subjectEletrocardiografiapt_PT
dc.titleEvolution, current challenges, and future possibilities in ECG biometricspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage34776pt_PT
oaire.citation.startPage34747pt_PT
oaire.citation.titleIEEE Accesspt_PT
oaire.citation.volume6pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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