Patient Confidential Data Hiding and Transmission System Using Amplitude Quantization in the Frequency Domain of ECG...

Area of Science:

• Biomedical Engineering
• Signal Processing
• Data Security

Background:

• Confidential data hiding and protection are critical in healthcare.
• Existing methods may compromise signal quality or data integrity.
• Secure transmission of sensitive patient information, like ECGs, requires robust solutions.

Purpose of the Study:

• To develop an amplitude quantization system in a transform domain for hiding patient information within ECG signals.
• To enhance the quality of hidden ECG signals using a non-linear model with a hiding state switch.
• To optimize the system for high signal-to-noise ratio (SNR) and minimal error metrics.

Main Methods:

• Implementation of an amplitude quantization system in the transform domain.
• Utilizing a non-linear model with a hiding state switch for signal enhancement.
• Application of particle swarm optimization (PSO) to solve the non-linear model and optimize performance.

Main Results:

• Achieved high signal-to-noise ratio (SNR) above 30 dB.
• Demonstrated minimal distortion in ECG signal shape with an Amplitude Similarity close to 1.
• Obtained a near-zero root mean square error (RMSE) for interval data, ensuring diagnostic accuracy.

Conclusions:

• The proposed transform domain amplitude quantization method effectively hides patient information in ECGs.
• The system maintains high signal quality and diagnostic relevance of the ECG.
• PSO optimization ensures excellent performance in terms of SNR, RMSE, and signal fidelity.