A novel framework for ECG-based identity management in mobile health monitoring, which updates gallery templates to address signal destabilization over time, demonstrated promising performance.
A novel framework for ECG-based biometric identity management shows promise in addressing signal destabilization over time and managing privacy in mobile health monitoring.
Abstract This work investigates the feasibility of ECG‐based identity management in mobile health monitoring applications. A body area network that operates in conjunction with ECG biometric recognition is explored for mobile monitoring of patients, rescuers, pilots, soldiers, or field agents in general. Among the major challenges of this technology is the stability of the signals over the monitoring duration. Time dependency is responsible for ECG destabilization, which becomes a significant issue for reliable monitoring. We propose a novel framework that addresses this inadequacy, by updating a gallery template when feature matching is compromised. In addition, strategies for tackling privacy issues in medical data management are proposed. A protocol level solution is discussed, to deal with the ethical issues of this technology. An automatic way of aggregating and managing personal information is presented, designated to operate on the basis of anonymity. The experimental performance measured over long‐ECG recordings demonstrates promising results. Copyright © 2010 John Wiley & Sons, Ltd.
Agrafioti et al. (Mon,) conducted a other in Mobile health monitoring. ECG biometric recognition framework was evaluated on Experimental performance over long-ECG recordings. A novel framework for ECG-based identity management in mobile health monitoring, which updates gallery templates to address signal destabilization over time, demonstrated promising performance.