Patient data hiding into ECG signal using watermarking in transform domain

Sanivarapu, Prasanth Vaidya; Rajesh, Kandala N. V. P. S.; Reddy, Niyoti

doi:10.1007/s13246-019-00838-2

Cited by 48 publications

(31 citation statements)

References 24 publications

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“…We clearly see from Table 3 that all the three methods can successfully extract all the embedded watermark bits when there is no attack. However, the proposed method achieved less than 5% BER under all the attack scenarios, while the mechanisms in [12] and [14] achieved BERs closer to 50%. This implies that the mechanisms in [12] and [14] completely fail under all the considered filtering attack scenarios.…”

Section: Simulation Resultsmentioning

confidence: 88%

“…However, the proposed method achieved less than 5% BER under all the attack scenarios, while the mechanisms in [12] and [14] achieved BERs closer to 50%. This implies that the mechanisms in [12] and [14] completely fail under all the considered filtering attack scenarios. From Tables 2 and 3, we can conclude that the proposed mechanism outperforms the methods in [12] and [14] in terms BER, while maintaining higher PSNR values.…”

Section: Simulation Resultsmentioning

confidence: 88%

“…The Table 2 shows the PSNR values obtained for all the three methods. One can clearly see from Table 2 that the PSNR values of the proposed mechanism are greater than that of the mechanisms in [12] and [14]. Further, it should be noted that our proposed approach does not embed a watermark bit in the medically significant region of the ECG signal.…”

Section: Simulation Resultsmentioning

confidence: 88%

“…We compared the robustness of the proposed mechanism against two recent ECG related mechanisms presented in [12] and [14]. The Table 2 shows the PSNR values obtained for all the three methods.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Another DWT based ECG data hiding mechanism is proposed in [12]. Here, first, the authors generated two dimensional (2D) data matrix from one dimensional ECG data, and using a third-party application, a QR code is obtained corresponding to the patients' information.…”

Section: A Data Hiding Methods Developed For Ecg Signalsmentioning

confidence: 99%

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Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

et al. 2020

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At present, a patient's demography, such as name, age, and gender are stored separately from the acquired electrocardiogram (ECG) signal. This multiple storage mechanisms can create a severe threat to the reliability of diagnostics if the link between the demography data and the ECG signal breaks, either intentionally or unintentionally. This issue has become more prominent in recent years due to the use of a large number of wearable devices for physiological signal collection, especially in remote or nonclinical settings. In order to address this problem, in this paper, we propose a novel mechanism to embed patient's information within an ECG signal without degrading the accuracy of the physiological information contained in the ECG signal. In this work, a methodology is presented to find the less-significant region of the ECG signal. Then, the patient information is hidden in this region by modifying the selected discrete cosine transform (DCT) coefficients of the signal using our proposed embedding and decoding algorithms. Moreover, the patient information hidden in the ECG signal is able to resist filtering attack, such as high-pass filtering, which generally occur with the ECG signal processing. This is achieved via the use of error buffers in the embedding algorithm. The proposed mechanism can extract the embedded patient information, either in the presence or without the filtering attack. Moreover, a specifically designed synchronization sequence is added to identify the patient data embedded regions of the ECG signal at the decoding end. Further, as a security measure, the embedded patient details are scrambled using a secret key to protect the privacy of the patient. Our evaluation demonstrates the usefulness of the proposed methodology in successfully embedding the patient information without distorting the important medical information in an ECG signal. INDEX TERMS ECG signal, information hiding, watermarking, physiological signal processing, discrete cosine transform.

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