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基于QR分解的心电图信号水印技术

Ecg signal watermarking using QR decomposition.

作者信息

Naderahmadian Yashar

机构信息

Department of Electrical Engineering, University of Guilan, Rasht, Iran.

出版信息

Phys Eng Sci Med. 2024 Dec;47(4):1677-1690. doi: 10.1007/s13246-024-01480-3. Epub 2024 Sep 12.

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.

摘要

本研究介绍了一种用于心电图(ECG)信号的新型水印技术。水印将关键信息嵌入到ECG信号中,可实现数据来源认证、所有权验证,并确保远程医疗、医学数据库、保险和法律程序等领域研究数据的完整性。该方法借鉴图像水印技术,将ECG信号转换为二维格式进行QR分解。然后将水印嵌入到所得R矩阵的第一行中。提出了三种实现方案:一种在空间域,另外两种在变换域,利用离散小波变换(DWT)来提高水印的不可感知性。对来自麻省理工学院-比赫心律失常数据库的真实ECG信号进行评估,并与现有方法进行比较,结果表明该方法实现了:(1)更高的峰值信噪比(PSNR),表明水印信号的变化最小;(2)在针对外部修改(如加性高斯白噪声(AWGN)、线路噪声和下采样)的鲁棒性测试中,误码率(BER)更低;(3)计算复杂度更低。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,在鲁棒性和不可感知性之间取得了平衡。所提出的方法有可能提高医疗保健和法律背景下ECG数据的安全性和真实性,同时其较低的计算复杂度增强了其实际适用性。

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本文引用的文献

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