Ecg signal watermarking using QR decomposition

IF 2.4 4区 医学 Q3 ENGINEERING, BIOMEDICAL Physical and Engineering Sciences in Medicine Pub Date : 2024-09-12 DOI:10.1007/s13246-024-01480-3
Yashar Naderahmadian
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Abstract

This study introduces a novel watermarking technique for electrocardiogram (ECG) signals. Watermarking embeds critical information within the ECG signal, enabling data origin authentication, ownership verification, and ensuring the integrity of research data in domains like telemedicine, medical databases, insurance, and legal proceedings. Drawing inspiration from image watermarking, the proposed method transforms the ECG signal into a two-dimensional format for QR decomposition. The watermark is then embedded within the first row of the resulting R matrix. Three implementation scenarios are proposed: one in the spatial domain and two in the transform domain utilizing discrete wavelet transform (DWT) for improved watermark imperceptibility. Evaluation on real ECG signals from MIT-BIH Arrhythmia database and comparison to existing methods demonstrate that the proposed method achieves: (1) higher Peak Signal-to-Noise Ratio (PSNR) indicating minimal alterations to the watermarked signal, (2) lower bit error rates (BER) in robustness tests against external modifications such as AWGN noise (additive white Gaussian noise), line noise and down-sampling, and (3) lower computational complexity. These findings emphasize the effectiveness of the proposed QR decomposition-based watermarking method, achieving a balance between robustness and imperceptibility. The proposed approach has the potential to improve the security and authenticity of ECG data in healthcare and legal contexts, while its lower computational complexity enhances its practical applicability.

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利用 QR 分解技术对心电图信号进行水印处理
本研究介绍了一种新型心电图(ECG)信号水印技术。水印技术将关键信息嵌入心电信号,从而实现数据来源认证、所有权验证,并确保远程医疗、医疗数据库、保险和法律诉讼等领域研究数据的完整性。受图像水印技术的启发,所提出的方法将心电图信号转换为二维格式,进行 QR 分解。然后将水印嵌入所得到的 R 矩阵的第一行。本文提出了三种实施方案:一种在空间域,另两种在变换域,利用离散小波变换(DWT)提高水印的不可感知性。通过对 MIT-BIH 心律失常数据库中的真实心电信号进行评估,并与现有方法进行比较,结果表明:(1) 拟议方法实现了更高的峰值信噪比 (PSNR),表明对水印信号的改动最小;(2) 在针对 AWGN 噪声(加性白高斯噪声)、线路噪声和下采样等外部改动的鲁棒性测试中实现了更低的误码率 (BER);(3) 降低了计算复杂度。这些发现强调了所提出的基于 QR 分解的水印方法的有效性,实现了鲁棒性和不可感知性之间的平衡。所提出的方法有望在医疗保健和法律领域提高心电图数据的安全性和真实性,同时其较低的计算复杂度也增强了其实际应用性。
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CiteScore
8.40
自引率
4.50%
发文量
110
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