Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW).
- Author:
Licai YANG
1
;
Jun SHEN
1
;
Shudi BAO
2
;
Shoushui WEI
1
Author Information
1. School of Control Science and Engineering, Shandong University, Jinan 250061, China.
2. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Biometric Identification;
methods;
Electrocardiography;
methods;
Humans;
Patient Identification Systems;
Pattern Recognition, Physiological
- From:
Journal of Biomedical Engineering
2013;30(5):976-981
- CountryChina
- Language:Chinese
-
Abstract:
To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.
