ECG-PPS: Privacy Preserving Disease Diagnosis and Monitoring System for Real-Time ECG Signal

TL;DR

This paper presents a real-time ECG monitoring system that ensures patient data privacy through advanced encryption techniques, enabling secure disease diagnosis, storage, visualization, and analysis without compromising confidentiality.

Contribution

The study introduces a novel ECG system integrating Fully Homomorphic Encryption for privacy-preserving real-time data analysis and storage, advancing secure medical monitoring technology.

Findings

Secure real-time ECG monitoring demonstrated

Encrypted statistical analysis performed successfully

Enhanced patient data privacy achieved

Abstract

This study introduces the development of a state of the art, real time ECG monitoring and analysis system, incorporating cutting edge medical technology and innovative data security measures. Our system performs three distinct functions thaat real time ECG monitoring and disease detection, encrypted storage and synchronized visualization, and statistical analysis on encrypted data. At its core, the system uses a three lead ECG preamplifier connected through a serial port to capture, display, and record real time ECG data. These signals are securely stored in the cloud using robust encryption methods. Authorized medical personnel can access and decrypt this data on their computers, with AES encryption ensuring synchronized real time data tracking and visualization. Furthermore, the system performs statistical operations on the ECG data stored in the cloud without decrypting it, using Fully Homomorphic Encryption (FHE). This enables privacy preserving data analysis while ensuring the security and confidentiality of patient information. By integrating these independent functions, our system significantly enhances the security and efficiency of health monitoring. It supports critical tasks such as disease detection, patient monitoring, and preliminary intervention, all while upholding stringent data privacy standards. We provided detailed discussions on the system's architecture, hardware configuration, software implementation, and clinical performance. The results highlight the potential of this system to improve patient care through secure and efficient ECG monitoring and analysis. This work represents a significant leap forward in medical technology. By incorporating FHE into both data transmission and storage processes, we ensure continuous encryption of data throughout its lifecycle while enabling real time disease diagnosis.