A protocol architecture for energy efficient and pervasive eHealth systems

The design of new and more pervasive healthcare systems has been fostered by the increased expectancy of life in the coming years. In this field, distributed and networked wireless embedded systems, such as Wireless Sensor Networks (WSNs), suit well with the requirements of continuous monitoring of aged people for their own safety, without affecting their daily activities. WSN4QoL is a Marie Curie project which involves academic and industrial partners from three EU countries, and aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. This paper focuses on presenting a protocol stack architecture designed to support the solutions proposed in that project to enhance energy efficiency.

[1]  Gregorio López,et al.  LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments , 2010, IEEE Transactions on Information Technology in Biomedicine.

[2]  Nuno Pereira,et al.  IEEE 802.15.4 and ZigBee as Enabling Technologies for Low-Power Wireless Systems with Quality-of-Service Constraints , 2013, Springer Briefs in Electrical and Computer Engineering.

[3]  Jun Sun,et al.  Compressive Network Coding for Approximate Sensor Data Gathering , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[4]  Luis Alonso,et al.  WSN4QoL: Wireless Sensor Networks for quality of life , 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013).

[5]  Cem Ersoy,et al.  Wireless sensor networks for healthcare: A survey , 2010, Comput. Networks.

[6]  Y. M. Huang,et al.  Pervasive, secure access to a hierarchical sensor-based healthcare monitoring architecture in wireless heterogeneous networks , 2009, IEEE Journal on Selected Areas in Communications.

[7]  Tzyy-Ping Jung,et al.  Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG Via Block Sparse Bayesian Learning , 2012, IEEE Transactions on Biomedical Engineering.

[8]  Anis Koubaa,et al.  A Time Division Beacon Scheduling Mechanism for IEEE 802.15.4/Zigbee Cluster-Tree Wireless Sensor Networks , 2007, 19th Euromicro Conference on Real-Time Systems (ECRTS'07).