By Topic

Resource-aware secure ECG healthcare monitoring through body sensor networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Honggang Wang ; UNIVERSITY OF MASSACHUSETTS, DARTMOUTH ; Dongming Peng ; Wei Wang ; Hamid Sharif
more authors

Real-time medical data about patients' physiological status can be collected simply by using wearable medical sensors based on a body sensor network. However, we lack an efficient, reliable, and secure BSN platform that can meet increasing needs in e-healthcare applications. Many such applications require a BSN to support multiple data rates with reliable and energyefficient data transmission. In this article we propose a secure and resource-aware BSN architecture to enable real-time healthcare monitoring, especially for secure wireless electrocardiogram data streaming and monitoring. A cross-layer framework was developed based on unequal resource allocation to support efficient biomedical data monitoring. In this framework important information (e.g., critical ECG data) is identified, and extra resources are allocated to protect it. Furthermore, BSN resource factors are exploited to guarantee a strict requirement of real-time performance. In this work we integrate biomedical information processing and transmission in a unified platform, where secure data transmission in a BSN proceeds with energy efficiency and minimum delay. In particular, we present a wearable ECG device consisting of small and low-power healthnode sensors for wireless three-lead ECG monitoring. Experimental and simulation results demonstrate that the proposed framework can support real-time wireless biomedical monitoring applications.

Published in:

IEEE Wireless Communications  (Volume:17 ,  Issue: 1 )