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Sparse Matrix for ECG Identification with Two-Lead Features
Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415669/ https://www.ncbi.nlm.nih.gov/pubmed/25961074 http://dx.doi.org/10.1155/2015/656807 |
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author | Tseng, Kuo-Kun Luo, Jiao Hegarty, Robert Wang, Wenmin Haiting, Dong |
author_facet | Tseng, Kuo-Kun Luo, Jiao Hegarty, Robert Wang, Wenmin Haiting, Dong |
author_sort | Tseng, Kuo-Kun |
collection | PubMed |
description | Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods. |
format | Online Article Text |
id | pubmed-4415669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-44156692015-05-10 Sparse Matrix for ECG Identification with Two-Lead Features Tseng, Kuo-Kun Luo, Jiao Hegarty, Robert Wang, Wenmin Haiting, Dong ScientificWorldJournal Research Article Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods. Hindawi Publishing Corporation 2015 2015-04-16 /pmc/articles/PMC4415669/ /pubmed/25961074 http://dx.doi.org/10.1155/2015/656807 Text en Copyright © 2015 Kuo-Kun Tseng et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Tseng, Kuo-Kun Luo, Jiao Hegarty, Robert Wang, Wenmin Haiting, Dong Sparse Matrix for ECG Identification with Two-Lead Features |
title | Sparse Matrix for ECG Identification with Two-Lead Features |
title_full | Sparse Matrix for ECG Identification with Two-Lead Features |
title_fullStr | Sparse Matrix for ECG Identification with Two-Lead Features |
title_full_unstemmed | Sparse Matrix for ECG Identification with Two-Lead Features |
title_short | Sparse Matrix for ECG Identification with Two-Lead Features |
title_sort | sparse matrix for ecg identification with two-lead features |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415669/ https://www.ncbi.nlm.nih.gov/pubmed/25961074 http://dx.doi.org/10.1155/2015/656807 |
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