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, and while most existing security solutions, such as cryptographic approaches, 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 electrocardiogram (ECG) signals in this paper. The signal is transformed into a 2D picture in this approach, and the frequency content of the image is extracted using the integer wavelet transform. Finally, the acquired coefficients are treated through 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 results of the experiments, we can infer that using the Integer wavelet transform allows for the generation of a watermarked signal that is practically identical to the host signal. The watermark's resistance to several attacks commonly used in watermarking is further confirmed by the robustness results.
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Data Availability Statements
The data used to support the findings of this study could be found freely here: https://archive.physionet.org/physiobank/database/mitdb/.
Abbreviations
- BER:
-
Bit error rate
- CPU:
-
Central processing unit
- Db:
-
Decibel
- DCT:
-
Discrete cosine transform
- DWT:
-
Discrete wavelet transform
- ECG:
-
Electrocardiogram
- GB:
-
Gigabyte
- GHZ:
-
Gigahertz
- HH:
-
High-high
- HL:
-
High-low
- IWT:
-
Integer wavelet transform
- LH:
-
Low–high
- LL:
-
Low-low
- MSB:
-
Most significant bit
- NCC:
-
Normalized cross correlation
- PRD:
-
Percentage residual difference
- PSNR:
-
Peak signal to noise ratio
- QR:
-
Quick response
- RAM:
-
Random access memory
- RLE:
-
Run length encoding
- RONI:
-
Region of non interest
- SSIM:
-
Structural similarity index measurement
- SVD:
-
Singular value decomposition
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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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Khaldi, A., Kafi, M.R. & Meghni, B. Electrocardiogram signal security by digital watermarking. J Ambient Intell Human Comput 14, 13901–13913 (2023). https://doi.org/10.1007/s12652-022-04101-7
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DOI: https://doi.org/10.1007/s12652-022-04101-7