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International Journal of Telemedicine and Applications
Volume 2008 (2008), Article ID 135808, 10 pages
Research Article

Real-Time and Secure Wireless Health Monitoring

1Department of Information Science, University Arkansas, Little Rock, AR 72204-1099, USA
2Teknoset Research, TUBITAK MAM, Gebze 41730, Turkey
3Mitsubishi Electric Research Labs, 201 Broadway Avenue, Cambridge, MA 02139, USA
4Computer Science and Engineering Department, School of Engineering Arizona State University Tempe, Arizona State University, Tempe, Arizona 85287, USA

Received 16 October 2007; Accepted 27 February 2008

Academic Editor: Sajid Hussain

Copyright © 2008 S. Dağtaş et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present a framework for a wireless health monitoring system using wireless networks such as ZigBee. Vital signals are collected and processed using a 3-tiered architecture. The first stage is the mobile device carried on the body that runs a number of wired and wireless probes. This device is also designed to perform some basic processing such as the heart rate and fatal failure detection. At the second stage, further processing is performed by a local server using the raw data transmitted by the mobile device continuously. The raw data is also stored at this server. The processed data as well as the analysis results are then transmitted to the service provider center for diagnostic reviews as well as storage. The main advantages of the proposed framework are (1) the ability to detect signals wirelessly within a body sensor network (BSN), (2) low-power and reliable data transmission through ZigBee network nodes, (3) secure transmission of medical data over BSN, (4) efficient channel allocation for medical data transmission over wireless networks, and (5) optimized analysis of data using an adaptive architecture that maximizes the utility of processing and computational capacity at each platform.