ECGSecT: secure transmission of ECG with undistorted R-peaks using reference less FIS for smart IoMT

Area of Science:

• Biomedical Engineering
• Information Security
• Digital Watermarking

Background:

• Cardiovascular diseases are increasing in young adults due to lifestyle factors.
• The rapid rise in electrocardiogram (ECG) data necessitates secure transmission and copyright protection.
• Existing methods lack robust security and real-time identity verification for medical data.

Purpose of the Study:

• To propose a secure transmission system for ECG data (ECGSecT) focusing on copyright protection.
• To implement real-time patient identity verification for Internet of Medical Things (IoMT) integration.
• To enhance watermarking performance using YCbCr domain processing.

Main Methods:

• ECG R-peaks extracted as watermark images.
• Patient's Aadhar card divided into two watermarks for identity verification.
• Secured Hash Algorithm (SHA) used for real-time identity verification.
• Reference-less Fuzzy Inference System (FIS) with NIQE and PIQE for balancing framework properties.

Main Results:

• Achieved a 12.94% improvement in imperceptibility.
• Demonstrated higher resilience and visual similarity compared to existing techniques.
• Successfully integrated real-time identity verification with secure ECG transmission.

Conclusions:

• The proposed ECGSecT system offers effective copyright and integrity protection for ECG data.
• The system provides robust, real-time authentication for IoMT applications.
• The approach enhances data security and privacy in remote patient monitoring.