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.

On the basis of the Karush–Kuhn–Tucker (KKT) theorem, a novel digital audio watermarking scheme is proposed. To guarantee the robustness of a watermark, this scheme embeds information into low‐frequency coefficients of audio's discrete wavelet transform. For the modification of low‐frequency amplitude, this study uses the KKT theorem to minimise the difference between the original and the watermarked coefficients. Accordingly, embedding strength is increased to enhance the most robustness of a watermarked audio under sufficient embedding capacity and audio quality. In addition, the proposed watermarking scheme can extract the hidden data without the knowledge of original audio signal. Experimental results indicate that the performance of the proposed scheme is mostly better than other amplitude modification methods.