Fiducial ECG-Based Biometry: Comparison of Classifiers and Dimensionality Reduction Methods

Luengo García, David and Meltzer, David (2019). Fiducial ECG-Based Biometry: Comparison of Classifiers and Dimensionality Reduction Methods. In: "42nd International Conference on Telecommunications and Signal Processing (TSP)", 1 al 3 de julio de 2019, Budapest (Hungría). pp. 552-556. https://doi.org/10.1109/TSP.2019.8768891.

Description

Title: Fiducial ECG-Based Biometry: Comparison of Classifiers and Dimensionality Reduction Methods
Author/s:
  • Luengo García, David
  • Meltzer, David
Item Type: Presentation at Congress or Conference (Article)
Event Title: 42nd International Conference on Telecommunications and Signal Processing (TSP)
Event Dates: 1 al 3 de julio de 2019
Event Location: Budapest (Hungría)
Title of Book: Proceedings of 42nd International Conference on Telecommunications and Signal Processing (TSP)
Date: 2019
Subjects:
Freetext Keywords: biometry; electrocardiogram (ECG); fiducial methods; dimensionality reduction; multi-class classification
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Teoría de la Señal y Comunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Biometry is becoming increasingly important in order to identify or authenticate individuals. Since the seminar work of Biel et at. in 1999 and 2001, the feasibility of using the electrocardiogram (ECG) for biometric recognition has been considered by several authors. Both fiducial methods, which are based on using fiducial points related to the detected QRS complexes, and non-fiducial methods, which do not require the extraction of the QRS complexes from the signals, have been considered. However, the feasibility of ECG-based biometry is still unclear, as the results from different studies are difficult to compare. In this paper, we concentrate on fiducial methods, comparing the performance of several classifiers and dimensionality reduction techniques on a publicly available dataset. Our results show that ECG-based biometry is indeed a feasible alternative to other widely used biometric traits, since an accuracy above 99.95% can be attained with the appropriate choice of the dimensionality reduction method and classifier.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2015-64835-C3-3-RUnspecifiedUnspecifiedTransformadas trigonométricas discretas para comunicaciones MIMO por la red eléctrica

More information

Item ID: 65123
DC Identifier: http://oa.upm.es/65123/
OAI Identifier: oai:oa.upm.es:65123
DOI: 10.1109/TSP.2019.8768891
Official URL: https://ieeexplore.ieee.org/abstract/document/8768891
Deposited by: Memoria Investigacion
Deposited on: 19 Feb 2021 11:08
Last Modified: 19 Feb 2021 11:09
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