ECG steganography using Contourlet transform for transmission of secured patient identity

ECG steganography hides patient data inside their ECG signal to ensure the protection of patient's identity. In this work, an attempt has been made to evaluate ECG Steganography where Quantization Index Modulation (QIM) method is used to embed patient data into the Contourlet transform coefficients of ECG image. Tompkins QRS detection algorithm is used to construct ECG image and which is decomposed into a series of multiscale, local and directional image expansion using contour segments. QIM scheme is applied on the appropriate coefficients of the selected frequency sub-bands. QIM divides the selected frequency sub-bands into non overlapping blocks of matrix size 2×2. Two quantizers are used to embed binary watermark 0 and 1. The reverse Contourlet transform provides the watermarked ECG image from which 1D stego-ECG signal is re-ordered. The proposed scheme retrieves the watermark without the need of cover image. The deterioration due to the modified coefficients are reduced using adaptive selection of a coefficient to hide watermark bit. The efficiency of ECG steganography is measured using imperceptibility of watermark and Bit Error Rate of the retrieved watermark. Similarity metrics such as Peak Signal to Noise ratio, Percentage Residual Difference and Kullback-Leibler distance are used to estimate the imperceptibility of watermark on the stego-ECG signal. It is demonstrated that the proposed approach provides higher imperceptibility and less Bit Error Rate in the retrieved watermark, which is closed to zero. ECG signals obtained from MITBIH normal sinus rhythm data base are used to evaluate the performance of the proposed ECG Steganography approach.