Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication

Although electrocardiogram (ECG) fluctuates over time and physical activity, some of its intrinsic measurements serve well as biometric features. Considering its constant availability and difficulty in being faked, the ECG signal is becoming a promising factor for biometric authentication. The major...

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Detalles Bibliográficos
Autores principales: Yang, Meixue, Liu, Bin, Zhao, Miaomiao, Li, Fan, Wang, Guoqing, Zhou, Fengfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3748040/
https://www.ncbi.nlm.nih.gov/pubmed/23977063
http://dx.doi.org/10.1371/journal.pone.0071523
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author Yang, Meixue
Liu, Bin
Zhao, Miaomiao
Li, Fan
Wang, Guoqing
Zhou, Fengfeng
author_facet Yang, Meixue
Liu, Bin
Zhao, Miaomiao
Li, Fan
Wang, Guoqing
Zhou, Fengfeng
author_sort Yang, Meixue
collection PubMed
description Although electrocardiogram (ECG) fluctuates over time and physical activity, some of its intrinsic measurements serve well as biometric features. Considering its constant availability and difficulty in being faked, the ECG signal is becoming a promising factor for biometric authentication. The majority of the currently available algorithms only work well on healthy participants. A novel normalization and interpolation algorithm is proposed to convert an ECG signal into multiple template cycles, which are comparable between any two ECGs, no matter the sampling rates or health status. The overall accuracies reach 100% and 90.11% for healthy participants and cardiovascular disease (CVD) patients, respectively.
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spelling pubmed-37480402013-08-23 Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication Yang, Meixue Liu, Bin Zhao, Miaomiao Li, Fan Wang, Guoqing Zhou, Fengfeng PLoS One Research Article Although electrocardiogram (ECG) fluctuates over time and physical activity, some of its intrinsic measurements serve well as biometric features. Considering its constant availability and difficulty in being faked, the ECG signal is becoming a promising factor for biometric authentication. The majority of the currently available algorithms only work well on healthy participants. A novel normalization and interpolation algorithm is proposed to convert an ECG signal into multiple template cycles, which are comparable between any two ECGs, no matter the sampling rates or health status. The overall accuracies reach 100% and 90.11% for healthy participants and cardiovascular disease (CVD) patients, respectively. Public Library of Science 2013-08-20 /pmc/articles/PMC3748040/ /pubmed/23977063 http://dx.doi.org/10.1371/journal.pone.0071523 Text en © 2013 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Yang, Meixue
Liu, Bin
Zhao, Miaomiao
Li, Fan
Wang, Guoqing
Zhou, Fengfeng
Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title_full Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title_fullStr Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title_full_unstemmed Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title_short Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication
title_sort normalizing electrocardiograms of both healthy persons and cardiovascular disease patients for biometric authentication
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3748040/
https://www.ncbi.nlm.nih.gov/pubmed/23977063
http://dx.doi.org/10.1371/journal.pone.0071523
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