[Paper Review] Embedding of Blink Frequency in Electrooculography Signal using Difference Expansion based Reversible Watermarking Technique

Nilanjan Dey, Prasenjit Maji+4 more|arXiv (Cornell University)|Mar 9, 2013

EEG and Brain-Computer Interfaces7 references16 citations

TL;DR

This paper proposes a reversible watermarking technique using Difference Expansion (DE) to embed blink frequency features from Electrooculography (EOG) signals, enabling secure transmission and integrity verification. The method embeds diagnostic parametric values directly into EOG signals with high robustness, achieving low bit error rate and high signal-to-noise ratio, ensuring accurate extraction without post-processing of the recovered signal.

ABSTRACT

In the past few years, like other fields, rapid expansion of digitization and globalization has influenced the medical field as well. For progress of diagnostic results most of the reputed hospitals and diagnostic centres all over the world have started exchanging medical information. In this proposed method, the calculated diagnostic parametric values of the original Electrooculography (EOG) signal are embedded as a watermark by using Difference Expansion (DE) algorithm based reversible watermarking technique. The extracted watermark provides the required parametric values at the recipient end without any post computation of the recovered EOG signal. By computing the parametric values from the recovered signal, the integrity of the extracted watermark can be validated. The time domain features of EOG signal are calculated for the generation of watermark. In the current work, various features are studied and two major features related to blink frequency are used to generate the watermark. The high Signal to Noise Ratio (SNR) and the Bit Error Rate (BER) claim the robustness of the proposed method.

Motivation & Objective

• To enable secure and reversible transmission of EOG signals in medical diagnostics.
• To embed diagnostic parametric values—specifically blink frequency—into EOG signals without altering the original signal's integrity.
• To ensure that the embedded watermark can be extracted without any post-processing of the recovered EOG signal.
• To validate the integrity of the extracted watermark by comparing it with parametric values computed from the recovered signal.
• To achieve high robustness and low error rates in watermark embedding and extraction for clinical reliability.

Proposed method

• The method uses Difference Expansion (DE) based reversible watermarking to embed diagnostic features into the EOG signal.
• Time-domain features of the EOG signal are computed to generate the watermark, with a focus on blink frequency-related parameters.
• The watermark embedding process modifies pixel-like intensity differences in the EOG signal using DE, preserving reversibility.
• The watermark is extracted without loss by reversing the DE process, allowing perfect reconstruction of the original EOG signal.
• The integrity of the extracted watermark is validated by recomputing the same parametric features from the recovered EOG signal.
• The approach ensures high Signal-to-Noise Ratio (SNR) and low Bit Error Rate (BER), indicating robustness.

Experimental results

Research questions

• RQ1 Can blink frequency features from EOG signals be embedded reversibly into the signal using a difference expansion-based technique?
• RQ2 Does the proposed method allow accurate extraction of embedded diagnostic values without post-processing of the recovered EOG signal?
• RQ3 How robust is the watermarking technique in terms of SNR and BER under signal transmission?
• RQ4 Can the integrity of the embedded watermark be verified by re-computing features from the recovered EOG signal?
• RQ5 What is the performance of the method in preserving signal quality and enabling lossless recovery?

Key findings

• The proposed method achieves a high Signal-to-Noise Ratio (SNR), indicating minimal degradation of the EOG signal after watermarking.
• The Bit Error Rate (BER) is low, confirming the reliability and accuracy of watermark extraction.
• The embedded diagnostic parametric values, particularly blink frequency, are successfully recovered without requiring post-processing of the reconstructed EOG signal.
• The integrity of the watermark is validated by re-computing the same features from the recovered EOG signal, showing consistency.
• The method ensures reversibility, allowing perfect reconstruction of the original EOG signal after watermark extraction.
• The technique demonstrates robustness and suitability for secure transmission of medical EOG data in clinical settings.