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Authors: Francisco Marques 1 ; Carlos Carreiras 2 ; André Lourenço 3 ; Ana Fred 4 and Rui Ferreira 5

Affiliations: 1 Instituto Superior Técnico, Portugal ; 2 Instituto de Telecomunicações, Portugal ; 3 Instituto de Telecomunicações and Instituto Superior de Engenharia de Lisboa, Portugal ; 4 Instituto Superior Técnico and Instituto de Telecomunicações, Portugal ; 5 Hospital de Santa Marta, Portugal

ISBN: 978-989-758-069-7

Keyword(s): ECG, Segmentation, Heartbeat, Feature Space, Dissimilarity Space, Dissimilarity Representation, Nearest Neighbor, Authentication, Identification, Biometrics.

Related Ontology Subjects/Areas/Topics: Applications ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Cardiovascular Signals ; Multimedia ; Multimedia Signal Processing ; Pattern Recognition ; Telecommunications

Abstract: Electrocardiogram (ECG) biometrics are a relatively recent trend in biometric recognition, with at least 13 years of development in peer-reviewed literature. Most of the proposed biometric techniques perform classification on features extracted from either heartbeats or from ECG based transformed signals. The best representation is yet to be decided. This paper studies an alternative representation, a dissimilarity space, based on the pairwise dissimilarity between templates and subjects´ signals. Additionally, this representation can make use of ECG signals sourced from multiple leads. Configurations of three leads will be tested and contrasted with single-lead experiments. Using the same k-NN classifier the results proved superior to those obtained through a similar algorithm which does not employ a dissimilarity representation. The best Authentication EER went as low as 1.53% for a database employing 503 subjects. However, the employment of extra leads did not prove itself adva ntageous. (More)

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Paper citation in several formats:
Marques, F.; Carreiras, C.; Lourenço, A.; Fred, A. and Ferreira, R. (2015). ECG Biometrics Using a Dissimilarity Space Representation.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 350-359. DOI: 10.5220/0005289303500359

@conference{biosignals15,
author={Francisco Marques. and Carlos Carreiras. and André Louren\c{C}o. and Ana Fred. and Rui Ferreira.},
title={ECG Biometrics Using a Dissimilarity Space Representation},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={350-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005289303500359},
isbn={978-989-758-069-7},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - ECG Biometrics Using a Dissimilarity Space Representation
SN - 978-989-758-069-7
AU - Marques, F.
AU - Carreiras, C.
AU - Lourenço, A.
AU - Fred, A.
AU - Ferreira, R.
PY - 2015
SP - 350
EP - 359
DO - 10.5220/0005289303500359

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