Diagnosis-Steganography-Transmission: An Innovative Integrated Paradigm for ECG Healthcare

Neerja Sahu, Dongming Peng, Hamid Sharif

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


The developing prominence of edge computing and Internet of Things-based wearables coupled with body sensors offer us a unique idea of integrating the Diagnosis, Steganography, and Transmission tasks in the healthcare domain. In this paper, we present an innovative Diagnosis-Steganography-Transmission architecture for health monitoring and real-time diagnosis especially designed for Coronary Artery Disease diagnostic purposes. The architecture works by extracting the patient’s health state by a real-time execution of a preliminary diagnostic algorithm in the local embedded computing platform before the ECG data are transmitted over wireless networks for further analysis. Local pre-diagnosis assists the operation of the communication module in deciding when and how much data should be transmitted and the given quality. The novelty of the proposed work is that the integration of diagnosis, steganography, and communication tasks in a unified platform, because unequal importance of physiological signals (e.g., ECG) feature offers computing distribution of diagnosis, UEP-based steganography, and UEP-based transmission are inherently connected with each other. Using the proposed framework, the steganography embedder, source encoder, and channel encoder in the communication module effectively reconfigure the intricacy of the control factors to match the energy constraints while maintaining the reconstruction quality of the medical signal. Moreover, the diagnosis module also reconfigures the complexity of the process of diagnosis to match the communication bandwidth constraints. By deep CNN-based ECG classification for local pre-diagnosis, an immense heap of energy-saving is created by a huge diminishing in the transmission overhead (up to 99.3% in typical application set-up) as compared to always-on communication.

Original languageEnglish (US)
Article number332
JournalSN Computer Science
Issue number4
StatePublished - Jul 2021


  • Diagnosis
  • Electrocardiogram (ECG)
  • Energy efficiency
  • Intermittent transmission
  • Steganography
  • Unequal error protection (UEP)

ASJC Scopus subject areas

  • Artificial Intelligence
  • General Computer Science
  • Computer Networks and Communications
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design


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