Mathivanan Ponnambalam, Edward Jero Sam, Ramu Palaniappan, Balaji Ganesh Athi
Department of Electronics and Communication Engineering, Velammal Engineering College, Chennai, India.
Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India.
Australas Phys Eng Sci Med. 2018 Dec;41(4):1057-1068. doi: 10.1007/s13246-018-0695-y. Epub 2018 Nov 5.
Connected health enables patient centric interventions resulting in better healthcare and hence better living. In order to accomplish this, bio-signals, medical and diagnosis information are shared and accessed by multiple actors and it is important to protect the privacy of patient data. Steganography is widely used to protect patient data by hiding it in the medical information. Current work investigates ECG steganography using Discrete Wavelet Transform (DWT) and Quick Response (QR) code. Steganography deteriorates the ECG signal and it is important to minimize this deterioration to preserve diagnosability. 1D ECG signal is converted to 2D ECG image and decomposed into sub-bands by subjecting it to DWT. The novelty of the proposed approach lies in converting the patient data into QR code and using it as watermark in ECG steganography. The QR code is embedded in the 2D image using additive quantization scheme. The performance of proposed method is measured using Peak Signal to Noise Ratio, Percentage Residual Difference and Kullback-Leibler distance. These metrics are used as a measure of imperceptibility while the data loss during retrieval is measured by Bit Retrieval Rate. The proposed method is demonstrated on normal ECG signals obtained from MIT-BIH database for different QR code versions. Metrics reveal that imperceptibility decreased for increasing patient data size and increasing scaling factors. Metrics were independent of the sub-band and the proposed method allows reliable patient data protection with full retrieval ability.
互联健康实现了以患者为中心的干预措施，从而带来更好的医疗保健，进而带来更好的生活。为了实现这一点，生物信号、医学和诊断信息由多个参与者共享和访问，保护患者数据的隐私非常重要。隐写术被广泛用于通过将患者数据隐藏在医学信息中来保护患者数据。当前的工作研究了使用离散小波变换（DWT）和快速响应（QR）码的心电图隐写术。隐写术会使心电图信号恶化，将这种恶化降至最低以保持可诊断性很重要。一维心电图信号被转换为二维心电图图像，并通过对其进行离散小波变换分解为子带。所提出方法的新颖之处在于将患者数据转换为QR码，并将其用作心电图隐写术中的水印。使用加法量化方案将QR码嵌入二维图像中。使用峰值信噪比、百分比残余差异和库尔贝克-莱布勒散度来衡量所提出方法的性能。这些指标用作不可感知性的度量，而检索期间的数据丢失则通过比特检索率来衡量。针对不同的QR码版本，在从麻省理工学院-贝斯以色列女执事医疗中心（MIT-BIH）数据库获得的正常心电图信号上演示了所提出的方法。指标显示，随着患者数据大小和缩放因子的增加，不可感知性降低。指标与子带无关，所提出的方法允许在具有完全检索能力的情况下可靠地保护患者数据。
