A Novel Dual Watermarking for ECG Signals with Improved Payload

The requirement to safeguard the integrity and validity of ECG signals drives the adoption of watermarking in these signals. Any tampering with or manipulation of ECG signals can result in inaccurate diagnosis or treatment because these signals are crucial for identifying and monitoring cardiovascular illnesses. Also, these signals are frequently sent via the internet, raising the possibility of unwanted access and manipulation. Hence, ECG signal watermarking is crucial for maintaining the reliability and accuracy of these signals in both clinical and research environments. This paper presents a novel ECG signal-based dual watermarking framework using a combination of two medical images: chest X-ray and PET image. A hybrid of DTCWT (Dual-Tree Complex Wavelet Transforms), HD (Hessenberg Decomposition), and MSVD (Multi-resolution singular valued decomposition) is used to embed the dual watermark. This hybrid method represented a significant enhancement not just in aspects of retrieving hidden data from the watermarked ECG signals but also in terms of its resistance to several attacks. To demonstrate the effectiveness of the watermarked ECG signal, we have evaluated the efficacy of the suggested technique using the PSNR, NC, KL, PRD and SSIM parameters. The recovered dual watermark is tested and found to be resistant to various attacks. The simulation results also show that the proposed methodology provided the best results of performance parameters, even when the size of the payload is large.