ECG Sensor Card with Evolving RBP Algorithms for Human Verification
It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-b...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-08-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/8/20730 |
| _version_ | 1798041094896746496 |
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| author | Kuo-Kun Tseng Huang-Nan Huang Fufu Zeng Shu-Yi Tu |
| author_facet | Kuo-Kun Tseng Huang-Nan Huang Fufu Zeng Shu-Yi Tu |
| author_sort | Kuo-Kun Tseng |
| collection | DOAJ |
| description | It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack—the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals. |
| first_indexed | 2024-04-11T22:16:42Z |
| format | Article |
| id | doaj.art-cd6a68eae5d54ea280b18fb391b4d053 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:16:42Z |
| publishDate | 2015-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cd6a68eae5d54ea280b18fb391b4d0532022-12-22T04:00:21ZengMDPI AGSensors1424-82202015-08-01158207302075110.3390/s150820730s150820730ECG Sensor Card with Evolving RBP Algorithms for Human VerificationKuo-Kun Tseng0Huang-Nan Huang1Fufu Zeng2Shu-Yi Tu3Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen 518055, ChinaDepartment of Mathematics, Tunghai University, Taichung 40704, TaiwanDepartment of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen 518055, ChinaDepartment of Mathematics, University of Michigan, Flint 48502, MI, USAIt is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack—the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals.http://www.mdpi.com/1424-8220/15/8/20730electrocardiogram verificationbiometricaccess control systemnon-stationarywaveletECG complexMIT-BIH database |
| spellingShingle | Kuo-Kun Tseng Huang-Nan Huang Fufu Zeng Shu-Yi Tu ECG Sensor Card with Evolving RBP Algorithms for Human Verification Sensors electrocardiogram verification biometric access control system non-stationary wavelet ECG complex MIT-BIH database |
| title | ECG Sensor Card with Evolving RBP Algorithms for Human Verification |
| title_full | ECG Sensor Card with Evolving RBP Algorithms for Human Verification |
| title_fullStr | ECG Sensor Card with Evolving RBP Algorithms for Human Verification |
| title_full_unstemmed | ECG Sensor Card with Evolving RBP Algorithms for Human Verification |
| title_short | ECG Sensor Card with Evolving RBP Algorithms for Human Verification |
| title_sort | ecg sensor card with evolving rbp algorithms for human verification |
| topic | electrocardiogram verification biometric access control system non-stationary wavelet ECG complex MIT-BIH database |
| url | http://www.mdpi.com/1424-8220/15/8/20730 |
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