Ecg signal watermarking using QR decomposition
- PMID: 39266907
- DOI: 10.1007/s13246-024-01480-3
Ecg signal watermarking using QR decomposition
Abstract
This study introduces a novel watermarking technique for electrocardiogram (ECG) signals. Watermarking embeds critical information within the ECG signal, enabling data origin authentication, ownership verification, and ensuring the integrity of research data in domains like telemedicine, medical databases, insurance, and legal proceedings. Drawing inspiration from image watermarking, the proposed method transforms the ECG signal into a two-dimensional format for QR decomposition. The watermark is then embedded within the first row of the resulting R matrix. Three implementation scenarios are proposed: one in the spatial domain and two in the transform domain utilizing discrete wavelet transform (DWT) for improved watermark imperceptibility. Evaluation on real ECG signals from MIT-BIH Arrhythmia database and comparison to existing methods demonstrate that the proposed method achieves: (1) higher Peak Signal-to-Noise Ratio (PSNR) indicating minimal alterations to the watermarked signal, (2) lower bit error rates (BER) in robustness tests against external modifications such as AWGN noise (additive white Gaussian noise), line noise and down-sampling, and (3) lower computational complexity. These findings emphasize the effectiveness of the proposed QR decomposition-based watermarking method, achieving a balance between robustness and imperceptibility. The proposed approach has the potential to improve the security and authenticity of ECG data in healthcare and legal contexts, while its lower computational complexity enhances its practical applicability.
Keywords: Discrete wavelet transform; ECG; QR decomposition; Watermarking.
© 2024. Australasian College of Physical Scientists and Engineers in Medicine.
Conflict of interest statement
Conflict of interest: Not applicable Ethical approval: This work does not contain any studies with human participants or animals performed by author. Code availability: Not applicable. Consent to participate: Not applicable Consent for publication: Not applicable.
Similar articles
-
QR code based patient data protection in ECG steganography.Australas Phys Eng Sci Med. 2018 Dec;41(4):1057-1068. doi: 10.1007/s13246-018-0695-y. Epub 2018 Nov 5. Australas Phys Eng Sci Med. 2018. PMID: 30397899
-
Blind video watermarking scheme for medical video authentication.Heliyon. 2023 Sep 7;9(9):e19809. doi: 10.1016/j.heliyon.2023.e19809. eCollection 2023 Sep. Heliyon. 2023. PMID: 37809959 Free PMC article.
-
Variational mode decomposition based ECG denoising using non-local means and wavelet domain filtering.Australas Phys Eng Sci Med. 2018 Dec;41(4):891-904. doi: 10.1007/s13246-018-0685-0. Epub 2018 Sep 6. Australas Phys Eng Sci Med. 2018. PMID: 30191539
-
Discrete wavelet transform and singular value decomposition based ECG steganography for secured patient information transmission.J Med Syst. 2014 Oct;38(10):132. doi: 10.1007/s10916-014-0132-z. Epub 2014 Sep 4. J Med Syst. 2014. PMID: 25187409
-
Improved ECG Watermarking Technique Using Curvelet Transform.Sensors (Basel). 2020 May 22;20(10):2941. doi: 10.3390/s20102941. Sensors (Basel). 2020. PMID: 32455935 Free PMC article.
References
-
- Nambakhsh MS, Ahmadian A, Ghavami M, Dilmaghani RS, Karimi-Fard S (2006) A novel blind watermarking of ecg signals on medical images using ezw algorithm. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 3274–3277. https://doi.org/10.1109/IEMBS.2006.259603
-
- Venkateswarlu L, Rao NV, Reddy BE (2017) A robust double watermarking technique for medical images with semi-fragility. In: 2017 International Conference on Recent Advances in Electronics and Communication Technology (ICRAECT), pp 126–131. https://doi.org/10.1109/ICRAECT.2017.40
-
- Bhalerao S, Ansari IA, Kumar A (2020) Reversible ecg data hiding: Analysis and comparison of ann, regression svm and random forest regression. In: Proceedings of the 2020 IEEE International Conference on Communication and Signal Processing, ICCSP 2020, pp 667–671. https://doi.org/10.1109/ICCSP48568.2020.9182219
-
- Natgunanathan I, Karmakar C, Rajasegarar S, Zong T, Habib A (2020) Robust patient information embedding and retrieval mechanism for ecg signals. IEEE Access 8:181233–181245. https://doi.org/10.1109/ACCESS.2020.3025533 - DOI
-
- Devi A, Shivakumar KB (2017) Novel Audio Steganography Technique for ECG Signals in Point of Care Systems (NASTPOCS). In: Proceedings - 2016 IEEE International Conference on Cloud Computing in Emerging Markets, CCEM 2016, pp 101–106. https://doi.org/10.1109/CCEM.2016.026