Intelligent Healthcare System Using Patients Confidential Data Communication in Electrocardiogram Signals

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

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

1 Scopus citations

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.

Original languageEnglish
Article number870844
JournalFrontiers in Aging Neuroscience
Volume14
DOIs
StatePublished - 20 04 2022

Bibliographical note

Publisher Copyright:
Copyright © 2022 Zhao, Chen, Chen, Tu, Yeh, Lin and Lu.

Keywords

  • dementia
  • multiple-coefficient
  • non-linear model
  • simulated annealing
  • transform domain

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