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利用心电图信号中患者保密数据通信的智能医疗系统。

Intelligent Healthcare System Using Patients Confidential Data Communication in Electrocardiogram Signals.

作者信息

Zhao Ming, Chen Shuo-Tsung, Chen Tzu-Li, Tu Shu-Yi, Yeh Cheng-Ta, Lin Fang-Yu, Lu Hao-Chun

机构信息

School of Computer Science, Yangtze University, Jingzhou, China.

Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan.

出版信息

Front Aging Neurosci. 2022 Apr 20;14:870844. doi: 10.3389/fnagi.2022.870844. eCollection 2022.

DOI:10.3389/fnagi.2022.870844
PMID:35527738
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9069238/
Abstract

With the advent of the aging era, healthcare and elderly care have become the focus of medical care, especially the care of the elderly with dementia. Patients' confidential data hiding is a useful technology for healthcare and patient information privacy. In this study, we implement an intelligent healthcare system using the multiple-coefficient quantization technology in transform domain to hide patients' confidential data into electrocardiogram (ECG) signals obtained by ECG sensor module. In embedding patients' confidential data, we first consider a non-linear model for optimizing the quality of the embedded ECG signals. Next, we apply simulated annealing (SA) to solve the non-linear model so as to have good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative RMSE (rRMSE). Accordingly, the distortion of the PQRST complexes and the ECG amplitude is very small so that the embedded confidential data can satisfy the requirements of physiological diagnostics. In end devices, one can receive the ECG signals with the embedded confidential data and without the original ECG signals. Experimental results confirm the effectiveness of our method, which remains high quality for each ECG signal with the embedded confidential data no matter how the quantization size Q is increased.

摘要

随着老龄化时代的到来,医疗保健和老年护理已成为医疗护理的重点,尤其是对老年痴呆症患者的护理。患者机密数据隐藏是一种用于医疗保健和患者信息隐私的有用技术。在本研究中,我们利用变换域中的多系数量化技术实现了一个智能医疗系统,将患者的机密数据隐藏到由心电图(ECG)传感器模块获取的心电图信号中。在嵌入患者机密数据时,我们首先考虑一个非线性模型来优化嵌入心电图信号的质量。接下来,我们应用模拟退火(SA)算法来求解该非线性模型,以获得良好的信噪比(SNR)、均方根误差(RMSE)和相对均方根误差(rRMSE)。因此,PQRST复合波和心电图幅度的失真非常小,使得嵌入的机密数据能够满足生理诊断的要求。在终端设备中,人们可以接收嵌入了机密数据的心电图信号,而无需原始心电图信号。实验结果证实了我们方法的有效性,无论量化大小Q如何增加,对于每个嵌入了机密数据的心电图信号,该方法都能保持高质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/85aee47bad55/fnagi-14-870844-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/7e8bde8cf8a1/fnagi-14-870844-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/955d2abc6e53/fnagi-14-870844-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/46b37bf75193/fnagi-14-870844-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/85aee47bad55/fnagi-14-870844-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/7e8bde8cf8a1/fnagi-14-870844-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/955d2abc6e53/fnagi-14-870844-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/46b37bf75193/fnagi-14-870844-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9f7/9069238/85aee47bad55/fnagi-14-870844-g004.jpg

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本文引用的文献

1
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2
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J Mach Learn Res. 2019;20:127.
3
Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard.根据工业标准优化小波 ECG 水印以保持测量性能。
Sensors (Basel). 2018 Oct 11;18(10):3401. doi: 10.3390/s18103401.
4
Hiding patients confidential datainthe ECG signal viaa transform-domain quantization scheme.通过变换域量化方案将患者机密数据隐藏于心电图信号中。
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5
Wavelet-based watermarking and compression for ECG signals with verification evaluation.基于小波的 ECG 信号水印和压缩及其验证评估。
Sensors (Basel). 2014 Feb 21;14(2):3721-36. doi: 10.3390/s140203721.
6
Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems.基于小波变换的心电信号隐写术在床边护理系统中保护患者机密信息的应用
IEEE Trans Biomed Eng. 2013 Dec;60(12):3322-30. doi: 10.1109/TBME.2013.2264539. Epub 2013 May 21.
7
Embedding patients confidential data in ECG signal for healthcare information systems.将患者机密数据嵌入心电图信号用于医疗保健信息系统。
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3891-4. doi: 10.1109/IEMBS.2010.5627671.
8
Wavelet transformation based watermarking technique for human electrocardiogram (ECG).基于小波变换的人体心电图(ECG)水印技术。
J Med Syst. 2005 Dec;29(6):589-94. doi: 10.1007/s10916-005-6126-0.
9
Watermarking medical signals for telemedicine.为远程医疗对医学信号进行水印处理。
IEEE Trans Inf Technol Biomed. 2001 Sep;5(3):195-201. doi: 10.1109/4233.945290.