title: ECG Sensor Card with Evolving RBP Algorithms for Human Verification.
abstract: 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.
authors: Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen 518055, China. kktseng@hitsz.edu.cn.
authors: Kuo-Kun
authors: KK
authors: Tseng
authors: Department of Mathematics, Tunghai University, Taichung 40704, Taiwan. nhuang@thu.edu.tw.
authors: Huang-Nan
authors: HN
authors: Huang
authors: Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen 518055, China. 12S051058@hitsz.edu.cn.
authors: Fufu
authors: F
authors: Zeng
authors: Department of Mathematics, University of Michigan, Flint 48502, MI, USA. sytu@umflint.edu.
authors: Shu-Yi
authors: SY
authors: Tu
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D004562:Electrocardiography / Q000295:instrumentation*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D058067:Wavelet Analysis; D055815:Young Adult
keywords: ECG complex; MIT-BIH database; access control system; biometric; electrocardiogram verification; non-stationary; wavelet