Performance of ZigBee Wireless Body Sensor Networks for ECG Signal Transmission under Maximum Payload Size

  • Hazha S. Yahia Department of Information Technology, Lebanese French University, Erbil, Kurdistan Region - F.R. Iraq. http://orcid.org/0000-0003-1255-1443
  • Wrya Monnet Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region - F.R. Iraq. http://orcid.org/0000-0002-7235-1905
Keywords: ECG Signals, Full packet length transmission, Performance comparison, Wireless Body Sensor Networks (WSBN), ZigBee

Abstract

Monitoring biomedical signals using Wireless Body Sensor Networks (WSBN) is a growing need. It can be used to provide health care for patients who are in high risk. The portability, light weight and nonintrusive sensors of WSBN suits the acquisition and transmission of Electrocardiogram (ECG) signals for monitoring and tracking purposes of patients with cardiovascular problems. The ZigBee wireless technology can be used for the transmission of ECG signals because of its sufficient available bandwidth, the ad hoc organization, relative long range coverage and low power consumption. Three different WBSN topologies are possible to connect the end devices (the embedded body sensors), the routers and the coordinators; these are star, tree and mesh. In this work the performances of the network, under full packet length transmissions for the above topologies, are analyzed. This has been done in terms of throughput, end-to-end delay and packet loss. The results shows that for the same coverage area a star configuration has the best performance in terms of throughput, end-to-end delay and packet loss. In fact, in star configuration and packet transmission without acknowledgment we can obtain approximately a TDMA channel performance in terms of throughput. While the mesh network is highly loaded with high end-to-end delays observed in the simulation.

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Author Biographies

Hazha S. Yahia, Department of Information Technology, Lebanese French University, Erbil, Kurdistan Region - F.R. Iraq.

Hazha Saeed Yahia is an Assistant lecturer at the Lebanese French University (LFU) and the Director of the Information System at LFU. She holds M.Sc. in Computer System Engineering at University of Kurdistan – Hawler in 2016

Wrya Monnet, Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region - F.R. Iraq.

Dr. Wrya received a postdoctoral degree in 2002 in telecommunication from INT Evry, France following a Ph.D. in Signal Processing in 2001 from University of Nice University of Nice Sophia-Antipolis, France and a DEA from INP-ENSEEIHT Toulouse, France. Since then he accumulated 10 years working experience in technological companies in France; 6 years of which as an R&D Engineer in audio signal processing and home automation systems, then 4 years in real-time embedded systems development for avionic navigation systems. Before going to France, he obtained his MSc in Electronics and Telecommunications from the University of Technology, Baghdad in 1991. Since 2012, he is an assistant professor in Department of Computer Science and Engineering in the University of Kurdistan Hewler. He worked as an Assistant lecturer in the College of Engineering, Electrical Engineering Department at the University of Salahaddin in Erbil from 1992 until 1995. He is interested in applied researches in Embedded Systems used in industry, signal processing in different areas: biomedical, Audio, Telecommunications, Navigation systems and connected information systems and robotics. [Click to see Academic Profile]

References

Nowak, D. (2012). Bridge between Industrial Wireless Sensor Network, Master Thesis. Krakow, Poland: AGH University of Science and Technology.

Yang, G., Aziz, O., Kwasnicki, R., Merrifield, R., Darzi, A., & Lo, B. (2006). Body Sensor Networks. Berlin, Germany: Springer, Wireless Sensor Networks. p. 1-3.

Yaqoob, M., Israr, I., Mustafa, M., & Rehman, A. (2013). Examination of IEEE 802.15.4 ZigBee multi-hop transmission in wireless. International Journal of Information Technology and Electrical Engineering, 2(1), 33-37.

LifeSync. (2016). Wireless ECG/EKG System. Available from: http://www.lifesynccorp.com/products/wirelessecgsystem. [Last accessed on 2016 Dec].

Our Products. IHealth Frontier. Available from: http://www.ihealthfrontier. com/home. [Last accessed on 2016 Dec].

Liang, X., & Balasingham, I. (2007). Performance analysis of the IEEE 802.15. 4 based ECG monitoring network. In: Wireless and Optical Communications. Montreal. Quebec, Canada: Research Gate. pp. 99-104.

Kaur, S., Singh, H., & Singh, G. (2004). Examine the performance of different topologies using OPNET 14.5 in ZigBee sensor network. International Journal of Computer Applications, 108(7), 1-5.

Golmie, N., Cypher, D., & Rebala, O. (2004). Performance evaluation of low rate WPANS for medical applications. In: MILCOM, IEEE Military Communication Conference. pp. 927-933.

Burchfield, T., Venkatesan, S., & Douglas, D. (2007). Maximizing throughput in ZigBee wireless networks through analysis, simulation and implementations. Wireless Monitoring Solutions, Signal Technology. A Crane Co.

Gertsch, M. (2009). The ECG Manual an Evidence-Based Approach. London: Springer.

Hammoodi, I. S., Stewart, B., & McMeekin, S. G. (2009). A Comprehensive Performance Study of OPNET Modeler for ZigBee Wireless Sensor Networks. IEEE Computer Society. pp. 357-362.

Kanna, R. (2011). Design of ZigBee Transceiver for IEEE 802.15.4 Using Matlab/Simulink, Master’s Thesis. Rourkela, Odisha, India: National Institute of Technology.

IEEE. (2011). Part 15.4: Low Rate Wireless Personal Area Networks (LR WPANs). New York, NY, USA: IEEE.

IEEE. (2004). Part 15.4: Wireless Medium Access Control (MAC)and Physical Layer (PHY) Specifications for Low Rate Wireless Personal Area Networks (LR WPANs). New York, NY, USA: The Institute of Electrical and Electronics Engineers, Inc.
Published
2017-12-08
How to Cite
Yahia, H., & Monnet, W. (2017, December 8). Performance of ZigBee Wireless Body Sensor Networks for ECG Signal Transmission under Maximum Payload Size. UKH Journal of Science and Engineering, 1(1), 19-25. https://doi.org/https://doi.org/10.25079/ukhjse.v1n1y2017.pp19-25
Section
Research Articles
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