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Wavelet-Based Watermarking and Compression for ECG Signals with Verification Evaluation

Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
Department of Exercise and Health Promotion, College of Education, Chinese Culture University (CCU) and Department of Neurosurgery, Lo-Hsu Foundation, Lotung Poh-Ai Hospital, Luodong, Yilan 265, Taiwan
Department of Applied Mathematics, Tunghai University, Taichung 40704, Taiwan
Department of Software Engineering, Xiamen University, Xiamen 361005, China
Department of Applied Mathematics, Tunghai University, Taichung 40704, Taiwan
Author to whom correspondence should be addressed.
Sensors 2014, 14(2), 3721-3736;
Received: 14 December 2013 / Revised: 6 February 2014 / Accepted: 18 February 2014 / Published: 21 February 2014
(This article belongs to the Special Issue Biomedical Sensors and Systems)
PDF [499 KB, uploaded 21 June 2014]


In the current open society and with the growth of human rights, people are more and more concerned about the privacy of their information and other important data. This study makes use of electrocardiography (ECG) data in order to protect individual information. An ECG signal can not only be used to analyze disease, but also to provide crucial biometric information for identification and authentication. In this study, we propose a new idea of integrating electrocardiogram watermarking and compression approach, which has never been researched before. ECG watermarking can ensure the confidentiality and reliability of a user’s data while reducing the amount of data. In the evaluation, we apply the embedding capacity, bit error rate (BER), signal-to-noise ratio (SNR), compression ratio (CR), and compressed-signal to noise ratio (CNR) methods to assess the proposed algorithm. After comprehensive evaluation the final results show that our algorithm is robust and feasible. View Full-Text
Keywords: integrating; watermarking; ECG; compression integrating; watermarking; ECG; compression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Tseng, K.-K.; He, X.; Kung, W.-M.; Chen, S.-T.; Liao, M.; Huang, H.-N. Wavelet-Based Watermarking and Compression for ECG Signals with Verification Evaluation. Sensors 2014, 14, 3721-3736.

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