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.
With the development of biometric verification, we proposed a new algorithm and personal mobile sensor card system for ECG verification. The proposed new mean-interval approach can identify the user quickly with high accuracy and consumes a small amount of flash memory in the microprocessor. The new framework of the mobile card system makes ECG verification become a feasible application to overcome the issues of a centralized database. For a fair and comprehensive evaluation, the experimental results have been tested on public MIT-BIH ECG databases and our circuit system; they confirm that the proposed scheme is able to provide excellent accuracy and low complexity. Moreover, we also proposed a multiple-state solution to handle the heat rate changes of sports problem. It should be the first to address the issue of sports in ECG verification.
With the rapid development of access control system based on biometric technologies, the conventional identification exposed more and more weakness while they are easy to be counterfeited and imitated. In this paper, we bring the access control systems with electrocardiogram identification into a practical application. Moreover, a new prompt based ECG algorithm are proposed to seek a more secure and accurate identification. In our evaluation, a hardware board were designed to verified its feasibility, then the analysis and comparison among various biometric identification and previous ECG identification researches were further disused as well. The result shown our proposed design could provide a more secure, low cost and convenient identification for access control system.
In this article, we use a self-synchronized watermark technology [7], to achieve the purpose of protection of electrocardiogram (ECG) signal. A Harr wavelet transform with 7 levels decomposition is adopted to transform the ECG signal and the synchronization code, combined with watermark, are quantized embedded in the low-frequency sub-band of level 7. The signal to noise ratio (SNR) between the embedded ECG and original one is greater than 30 such that the difference between these two ECG signals is very small and negligible in general. To test the robustness under the network transfer of ECG data, a white noise attack with various strengths is simulated that the bit error rate is quite small unless the SNR of the noise is very large. This study confirms the use of waveletbased quantization watermarking scheme on ECG signal for patient protection is adequate.
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