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ECG Signal Protection for Telemedicine Applications

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Abstract

Medical data is transferred between hospitals and healthcare providers via telemedicine to improve patient care. This transfer exposes medical data to a number of security risks. While most existing security solutions, such as cryptographic techniques, protect data from unauthorized access, this protection is only effective when the data is encrypted. In this context, we present a frequency-domain watermarking method for hiding electronic patient records in their associated ECG signals in this paper. The signal is transformed into a 2D image in this method, and the frequency content of the image is extracted using the integer wavelet transform. Finally, the acquired coefficients are subjected to Schur decomposition, and the watermark bits are integrated by altering the least significant bit of the generated Eigen values. We used the ECG data from the MIT-BIH Arrhythmia Database to test the suggested method. Based on the outcomes of the studies, we can conclude that using the Integer wavelet transform allows for the generation of a watermarked signal that is nearly identical to the host signal. The watermark's resistance to various attacks commonly used in watermarking is also confirmed by the robustness results.

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Data Availability

The data used to support the findings of this study could be found freely here: https://archive.physionet.org/physiobank/database/mitdb/

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Acknowledgements

This work was supported by "La Direction Générale de la Recherche Scientifique et du Développement Technologique (DGRSDT)" of Algeria.

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Authors and Affiliations

  1. Computer Science Department, Faculty of Sciences and Technology, Artificial Intelligence and Information Technology Laboratory (LINATI), University of Kasdi Merbah, 30000, Ouargla, Algeria

    Khaldi Amine

  2. Electronics Department, Faculty of Sciences and Technology, Electrical Engineering Laboratory, University of Kasdi Merbah, 30000, Ouargla, Algeria

    Kafi Med Redouane

  3. Electronics Department, Faculty of Engineering Sciences, Laboratories of Automation and Signals of Annaba (LASA), Badji Mokhtar Annaba University, 23000, Annaba, Algeria

    Zermi Narima

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Correspondence to Khaldi Amine.

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Amine, K., Med Redouane, K. & Narima, Z. ECG Signal Protection for Telemedicine Applications. Circuits Syst Signal Process 41, 5856–5871 (2022). https://doi.org/10.1007/s00034-022-02063-x

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