QR code based patient data protection in ECG steganography.

Area of Science:

• Biomedical Engineering
• Digital Health
• Information Security

Background:

• Connected health relies on sharing sensitive patient data, necessitating robust privacy protection methods.
• Steganography is crucial for safeguarding medical information, but it can degrade signal quality, impacting diagnostic accuracy.
• Existing steganography techniques require improvement to balance data security with signal integrity.

Purpose of the Study:

• To develop and evaluate a novel ECG steganography technique for secure patient data transmission.
• To minimize signal deterioration in electrocardiogram (ECG) data while embedding patient information.
• To assess the effectiveness of using Quick Response (QR) codes as watermarks in ECG steganography.

Main Methods:

• Converting 1D ECG signals into 2D ECG images for processing.
• Applying Discrete Wavelet Transform (DWT) to decompose ECG images into sub-bands.
• Embedding patient data, encoded as QR codes, into the DWT sub-bands using an additive quantization scheme.

Main Results:

• The proposed method demonstrated reliable patient data protection with full retrieval capability.
• Imperceptibility of the embedded data decreased with larger patient data sizes and scaling factors.
• Performance metrics, including Peak Signal to Noise Ratio and Bit Retrieval Rate, were used to evaluate imperceptibility and data loss.

Conclusions:

• The novel ECG steganography approach effectively protects patient data using QR codes and DWT.
• The method offers a viable solution for secure data handling in connected health applications.
• Further research can optimize embedding parameters to enhance imperceptibility for larger data volumes.