The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Accurate and Energy Efficient ECG Analysis Method for ECG Monitoring System

  • Zeng, Min (Department of Computer Engineering, Chosun University) ;
  • Lee, Jeong-Gun (Department of Computer Engineering, Hallym University) ;
  • Chung, Il-Yong (Department of Computer Engineering, Chosun University) ;
  • Lee, Jeong-A (Department of Computer Engineering, Chosun University)
  • Received : 2012.02.29
  • Accepted : 2012.04.30
  • Published : 2012.05.30
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Abstract

This paper proposes an energy efficient ECG monitoring system by putting some intelligence on the sensor node to reduce the number of transmissions. The sensor node is mostly put into the processing mode and just connects the base station when necessary. Therefore, the transmission energy is greatly reduced while the energy for processing is increased a little bit. Our proposed ECG analysis method classifies ECG cycles by computing the Euclidean distance between the sensed ECG cycle and the reference ECG cycle. This work is a detailed and full explanation of our former work. Extended experimental results show that the proposed trade is very effective in saving energy and the Euclidean distance based classification method is accurate. Furthermore, the PowerTOSSIM energy simulation method is also demonstrated as very accurate in evaluating the energy consumption of the sensor node in our application scenario.

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References

  1. M. Zeng, I. Y. Chung, J. A. Lee, J. G. Lee, "An on-node intelligence based energy efficient ECG monitoring system," in Proc. of 2011 International Conference on ICT Convergence (ICTC), pp. 401-405, Sep. 2011.
  2. J. M. Gu, W. M. Lim, K. S. Yeo, M. A. Do, and C. C. Boon, "Low power transmitter design for BAN," in Proc. of Biomedical Circuits and Systems Conference, pp. 175 - 178, Nov. 2007.
  3. A. Wong, G. Kathiresan, T. Chan, O. Eljamaly, O. Omeni, D. McDonagh, A. Burdett, and C. Toumazou, "A 1V wireless transceiver for an ultra low power SoC for biotelemetry applications," Solid-State Circuits, vol. 43, no. 7, pp. 1511-1521, 2008. https://doi.org/10.1109/JSSC.2008.923717
  4. C. Park, P. H. Chou, "Eco: ultra-wearable and expandable wireless sensor platform," in Proc. of International Workshop on Wearable and Implantable Body Sensor Networks, pp. 162-165, Apr. 2006.
  5. H. M. Li, and J. D. Tan, "Medium access control for body sensor networks," in Proc. of 16th International Conference on Computer Communications and Networks, pp. 210-215, Aug. 2007.
  6. X. L. Wu B. J. d'Autriol, J. S. Cho, S. Y. Lee, "Optimal routing in sensor networks for in-home health monitoring with multi-factor considerations," in Proc. of 6th Annual IEEE International Conference on Pervasive Computing and Communications, pp. 720-725, Mar. 2008.
  7. D. Lee, S. Bhardwaj, E. Alasaarela, and W. Chung, "An ECG analysis on sensor node for reducing traffic overload in u-healthcare with wireless sensor network," in Proc. of 6th IEEE Sensors Conference, pp. 256-259, Oct. 2007.
  8. M. Zeng, J. G. Lee, G. S. Choi, and J. A. Lee, "Intelligent sensor node based a low power ECG monitoring system," IEICE Electron Express, vol. 6, no. 9, pp. 560-565, 2009. https://doi.org/10.1587/elex.6.560
  9. J. P. Burg, "Maximum entropy spectral analysis," PhD dissertation, Department of Geophysics, Stanford University, May. 1975.
  10. D. F. Ge, N. Srinivasan, and S. M. Krishnan, "Cardiac arrhythmia classification using autoregressive modeling," Biomedical Engineering Online, vol. 1, no. 5, pp. 1-12, 2002. https://doi.org/10.1186/1475-925X-1-1
  11. D. Gay, P. Levis, and R.von Behren, "The nesC language: a holistic approach to networked embedded systems," in Proc. of the ACM SIGPLAN conference on Programming language design and implementation, Jun. 2003.
  12. J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, "System architecture directions for networked sensors," in Proc. of 9th International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 93-104, 2000.
  13. Hybus mote. www.hybus.net
  14. M. Zeng, and J. A. Lee, "Power efficient classification method for sensor nodes in BSN based ECG monitoring system," The Journal of Korea Information and Communication Society, vol. 35, no. 9, pp. 1322-1329, 2010.