Patient data hiding into ECG signal using watermarking in transform domain

Electrocardiogram (ECG) watermarking provides secure communication of patient information lies in a 1D-ECG signal. The primary challenge in ECG watermarking is the deterioration of an ECG signal which causes the loss and impotence to extract patient information. This paper proposes a wavelet method based watermarking scheme for patient information hiding in the ECG as a QR image. Here, we first convert the 1D-ECG signal to 2D-ECG image using the Pan-Tompkins algorithm. We use a wavelet transform to decompose 2D-ECG image. Wavelet analysis can capture the subtle underlying information of the ECG. Then we further decompose the detail coefficient of wavelet and the QR image using QR decomposition for embedding data. The embedding factor value calculation is adaptive by harnessing the entropy value of the signal. The hidden data is easily extractable with no distortion at the extractor side. The ECG data we use in this paper is from the MIT-BIH database. The results on this dataset suggest that our proposed approach is useful in patient information data hiding scheme in ECG. The proposed method outperforms the state-of-the-art.