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Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network

  • Mobile & Wireless Health
  • Published:
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Abstract

The paper presents a network coded cooperative communication (NC-CC) enabled wireless hospital sensor network architecture for monitoring health as well as postural activities of a patient. A wearable device, referred as a smartband is interfaced with pulse rate, body temperature sensors and an accelerometer along with wireless protocol services, such as Bluetooth and Radio-Frequency transceiver and Wi-Fi. The energy efficiency of wearable device is improved by embedding a linear acceleration based transmission duty cycling algorithm (NC-DRDC). The real-time demonstration is carried-out in a hospital environment to evaluate the performance characteristics, such as power spectral density, energy consumption, signal to noise ratio, packet delivery ratio and transmission offset. The resource sharing and energy efficiency features of network coding technique are improved by proposing an algorithm referred as network coding based dynamic retransmit/rebroadcast decision control (LA-TDC). From the experimental results, it is observed that the proposed LA-TDC algorithm reduces network traffic and end-to-end delay by an average of 27.8% and 21.6%, respectively than traditional network coded wireless transmission. The wireless architecture is deployed in a hospital environment and results are then successfully validated.

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References

  1. He, T., Krishnamurthy, S., Stankovic, J.A., Abdelzaher, T., Luo, L., Stoleru, R., Yan, T., Gu, L., Hui, J. and Krogh, B (2004) Boston. Energy-efficient surveillance system using wireless sensor networks. In Proceedings of the 2nd international conference on Mobile systems, applications, and services (pp. 270–283). ACM

  2. Xu, N., Rangwala, S., Chintalapudi, K.K., Ganesan, D., Broad, A., Govindan, R. and Estrin, D (2004) Maryland. A wireless sensor network for structural monitoring. In Proceedings of the 2nd international conference on Embedded networked sensor systems (pp. 13–24). ACM.

  3. Akyildiz, I.F., Weilian, S., Sankarasubramaniam, Y., and Cayirci, E., Wireless sensor networks: a survey. Computer networks. 38(4):393–422, 2002.

    Article  Google Scholar 

  4. Nadeem, A., Hussain, M.A., Owais, O., Salam, A., Iqbal, S., and Ahsan, K., Application specific study, analysis and classification of body area wireless sensor network applications. Computer Networks. 83:363–380, 2015.

    Article  Google Scholar 

  5. İlhan, İ., Yıldız, İ., and Kayrak, M., Development of a wireless blood pressure measuring device with smart mobile device. Computer methods and programs in biomedicine. 125:94–102, 2016.

    Article  PubMed  Google Scholar 

  6. Ntouni, G.D., Lioumpas, A.S., and Nikita, K.S., Reliable and energy-efficient Communications for Wireless Biomedical Implant Systems. IEEE Journal of Biomedical and Health Informatics. 18(6):1848–1856, 2014.

    Article  PubMed  Google Scholar 

  7. Kirby, K.K., Hours per patient day: not the problem, nor the solution. Nursing Economics. 33(1):64, 2015.

    PubMed  Google Scholar 

  8. Ostovari, P., Wu, J., and Khreishah, A., Network coding techniques for wireless and sensor networks. In: The art of wireless sensor networks. Springer, Berlin Heidelberg, pp. 129–162, 2014.

    Chapter  Google Scholar 

  9. Ibrahim, A.S., Sadek, A.K., Su, W. and Liu, K.R (2006) California. SPC12–5: relay selection in multi-node cooperative communications: when to cooperate and whom to cooperate with? Global Telecommunications Conference, 1–5.

  10. Marchenko, N., Andre, T., Brandner, G., Masood, W., and Bettstetter, C., An experimental study of selective cooperative relaying in industrial wireless sensor networks. IEEE Transactions on Industrial Informatics. 10(3):1806–1816, 2014.

    Article  Google Scholar 

  11. Huang, Y.M., Hsieh, M.Y., Chao, H.C., Hung, S.H., and Park, J.H., Pervasive, secure access to a hierarchical sensor-based healthcare monitoring architecture in wireless heterogeneous networks. IEEE Journal on Selected Areas in Communications. 27(4):400–411, 2009.

    Article  Google Scholar 

  12. Sliman, J.B., Song, Y.Q., Koubâa, A. and Frikha, M (2009) Portugal. A three-tiered architecture for large-scale wireless hospital sensor networks. In Workshop Mobi Health Inf in conjunction with BIOSTEC: 64.

  13. Chipara, Octav, Chenyang Lu, Thomas C. Bailey, and Gruia-Catalin Roman (2010) Switzerland. Reliable clinical monitoring using wireless sensor networks: experiences in a step-down hospital unit. In Proceedings of the 8th ACM conference on embedded networked sensor systems, ACM: 155–168.

  14. Nguyen, D., Tran, T., Nguyen, T., and Bose, B., Wireless broadcast using network coding. IEEE Transactions on Vehicular technology. 58(2):914–925, 2009.

    Article  Google Scholar 

  15. Zhang, Z., Lv, T., Su, X. and Gao, H (2011) Japan. Dual XOR in the air: A network coding based retransmission scheme for wireless broadcasting. IEEE International Conference on Communications (ICC):1–6.

  16. Long, S., Liu, J., Jiang, G., and Gao, Y., Low power consumption data retransmission strategy in WSNs based on network coding. Transducer and Microsystem Technologies. 32(8):35–38, 2013.

    Google Scholar 

  17. Zhou, Z.-H., and Zhou, L., Efficient loss recovery based on network coding in multicast networks. Journal of Electronics and Information Technology. 34(8):1962–1967, 2012.

    Article  Google Scholar 

  18. Zhu, C., Zhu, Y. and Li, L (2015) Network coding-based real-time retransmission scheme in wireless sensor networks. International Journal of Distributed Sensor Networks, p. 116.

  19. Rout, R.R., and Ghosh, S.K., Enhancement of lifetime using duty cycle and network coding in wireless sensor networks. IEEE Transactions on Wireless Communications. 12(2):656–667, 2013.

    Article  Google Scholar 

  20. Lin, F., Wang, A., Cavuoto, L. and Xu, W (2016) Towards Unobtrusive Patient Handling Activity Recognition for Reducing Injury Risk among Caregivers. IEEE J Biomed Health Inform. PP (99), pp. 1–1

  21. Prakash, R., Balaji Ganesh, A., and Girish, S.V., Cooperative wireless network control based health and activity monitoring system. Journal of Medical Systems. 40(10):1–14, 2016.

    Article  Google Scholar 

  22. Ammari, H.M., The art of wireless sensor networks. Springer, 2013.

  23. Webster, J.G., and Eren, H. (Eds.), Measurement, instrumentation, and sensors handbook: spatial, mechanical, thermal, and radiation measurement. Vol. 1. CRC press, 2014.

  24. Burns, A., Greene, B.R., McGrath, M.J., O'Shea, T.J., Kuris, B., Ayer, S.M., Stroiescu, F., and Cionca, V., SHIMMER™–a wireless sensor platform for noninvasive biomedical research. IEEE Sensors Journal. 10(9):1527–1534, 2010.

    Article  Google Scholar 

  25. Pereira, O.R., Caldeira, J.M., Shu, L., and Rodrigues, J.J., An efficient and low cost windows mobile BSN monitoring system based on TinyOS. Telecommunication Systems. 55(1):115–124, 2014.

    Article  Google Scholar 

  26. Giansanti, D., Morelli, S., Maccioni, G., and Brocco, M., Design, construction and validation of a portable care system for the daily tele rehabiliatation of gait. Computer methods and programs in biomedicine. 112(1):146–155, 2013.

    Article  PubMed  Google Scholar 

  27. Yu, L., Xiong, D., Guo, L., and Wang, J., A remote quantitative Fugl-Meyer assessment framework for stroke patients based on wearable sensor networks. Computer methods and programs in biomedicine. 128:100–110, 2016.

    Article  PubMed  Google Scholar 

  28. Antonopoulos, C.P., and Voros, N.S., Resource efficient data compression algorithms for demanding, WSN based biomedical applications. Journal of biomedical informatics. 59:1–14, 2016.

    Article  PubMed  Google Scholar 

  29. Wunderlich, S., Welpot, M., and Gaspard, I., Indoor radio channel modeling and mitigation of fading effects using linear and circular polarized antennas in combination for smart home system at 868 MHz. Advances in Radio Science. 12(3):53–59, 2014.

    Article  Google Scholar 

  30. Seidel, S.Y., and Rappaport, T.S., 914 MHz path loss prediction models for indoor wireless communications in multifloored buildings. IEEE Transactions on Antennas and Propagation. 40(2):207–217, 1992.

    Article  Google Scholar 

  31. Zagar, D., Horvat, G. and Rimac-Drlje, S (2013) Fade depth prediction using human presence for real life WSN deployment. Radioengineering.

    Google Scholar 

  32. MSP430™ SoC With RF Core,“SLAS554H (2013) Datasheet: ECCN 5E002 TSPARev [Online]. Available:http://www.ti.com.cn/cn/lit/ds/symlink/cc430f6137.pdf

  33. CC1101 “SWRS061I” Datasheet: Low-Power Sub-1 GHz RF Transceiver, [Online] Available:http://www.ti.com/lit/ds/swrs061i/swrs061i.pdf

  34. CC3200 SimpleLink™ Wi-Fi and Internet-of-Things Solution, a Single-Chip Wireless MCU” Datasheet: Swas032f (July 2013) Revised (2015) [Online] Available:http://www.ti.com/lit/ds/symlink/cc3200.pdf

  35. MAX30100 Datasheet: “Pulse Oximeter and Heart-Rate Sensor IC For Wearable Health” [Online] Available: https://datasheets.maximintegrated.com/en/ds/MAX30100.pdf

  36. MA100 Datasheet: “Thermo metrics Biomedical Chip Thermistors” [Online] Available: http://www.ge-mcs.com/download/temperature/920_321a.pdf

  37. ADXL335 Datasheet: “Small, Low Power, 3-Axis ±3g Accelerometer” [Online] Available: https://www.sparkfun.com/datasheets/Components/SMD/adxl335.pdf

  38. CC2541 “SWRS128 ” Datasheet: SimpleLink™ Bluetooth® Low Energy Wireless MCU, [Online] Available:http://www.ti.com/lit/ds/symlink/cc2541-q1.pdf

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Acknowledgements

The authors gratefully acknowledge the financial support from Science for Equity Empowerment and Development Division under Department of Science and Technology, New Delhi, India by sanctioning a project - File No.: SSD/TISN/047/2011-TIE (G) to Velammal Engineering College, Chennai.

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Correspondence to A. Balaji Ganesh.

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All authors of this manuscript declare as they do have no conflict of interest with any Laboratory, Funding Source or an Individual.

Research involving human participants and/or animals and informed consent

The parameters measured are pulse rate, body temperature and acceleration (body movement) by using non-invasive sensors and collected information not used for any prescription and diagnostic purposes. Further, Informed consent was obtained from all individual participants included in the study.

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This article is part of the Topical Collection on Mobile & Wireless Health

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Prakash, R., Balaji Ganesh, A. & Sivabalan, S. Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network. J Med Syst 41, 72 (2017). https://doi.org/10.1007/s10916-017-0721-8

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