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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/656807 |
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| _version_ | 1832551667498745856 |
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| author | Kuo-Kun Tseng Jiao Luo Robert Hegarty Wenmin Wang Dong Haiting |
| author_facet | Kuo-Kun Tseng Jiao Luo Robert Hegarty Wenmin Wang Dong Haiting |
| author_sort | Kuo-Kun Tseng |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-4bde6ca4689e48ba8266f90de2341877 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-4bde6ca4689e48ba8266f90de23418772025-02-03T06:00:48ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/656807656807Sparse Matrix for ECG Identification with Two-Lead FeaturesKuo-Kun Tseng0Jiao Luo1Robert Hegarty2Wenmin Wang3Dong Haiting4Shenzhen Key Laboratory of Internet Information Collaboration, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, Guangdong 518052, ChinaShenzhen Key Laboratory of Internet Information Collaboration, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, Guangdong 518052, ChinaSchool of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool L3 3AF, UKSchool of Electronic and Communication, Shenzhen Graduate School, Peking University, Shenzhen, Guangdong 518052, ChinaShenzhen Key Laboratory of Internet Information Collaboration, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, Guangdong 518052, ChinaElectrocardiograph (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.http://dx.doi.org/10.1155/2015/656807 |
| spellingShingle | Kuo-Kun Tseng Jiao Luo Robert Hegarty Wenmin Wang Dong Haiting Sparse Matrix for ECG Identification with Two-Lead Features The Scientific World Journal |
| 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 |
| url | http://dx.doi.org/10.1155/2015/656807 |
| work_keys_str_mv | AT kuokuntseng sparsematrixforecgidentificationwithtwoleadfeatures AT jiaoluo sparsematrixforecgidentificationwithtwoleadfeatures AT roberthegarty sparsematrixforecgidentificationwithtwoleadfeatures AT wenminwang sparsematrixforecgidentificationwithtwoleadfeatures AT donghaiting sparsematrixforecgidentificationwithtwoleadfeatures |