Wireless Personal Communications

, Volume 103, Issue 3, pp 2229–2244 | Cite as

Dual Band RFID-Based Blood Glucose Monitoring System in Wireless Sensor Network Platform

  • Shabinar Abdul Hamid
  • Widad IsmailEmail author
  • Che Zalina Zulkifli
  • Samihah Abdullah


Accurate record on the patient’s glucose information is crucial to assist doctors in decision making and prescribing correct medication. In this paper, a dual band Radio-Frequency Identification (RFID) system embedded with glucose meter was developed by integrating a 920 MHz passive interrogator into the 2.45 GHz active tag to enable automatic patient detection, wireless data recording and monitoring in dense hospital environment with frequent usage. The real-time experimental results indicate that the developed embedded RFID system in the multihop wireless sensor network is able to maintain the integrity of the glucose data according to the identification of the patient until the data are successfully recorded to the remote host system. Design of Experiment method is performed to determine the factors that influenced the throughput performance of the system. Comparisons made between existing non-embedded RFID system and the proposed embedded RFID system. The three factors investigated were the packet length, number of hops and type of RFID. The statistical analysis showed that the packet length as the main factor influencing the throughput performance. The results showed that the larger packets increase the throughput, while the number of hops contributes more to the decreasing effect of the throughput compared to the implementation of embedded RFID system.


DOE Dual band RFID Blood glucose monitoring 



The authors would like to thank the FRGS Grant (6071187) and RUI for sponsoring the development of the in house built in devices and Auto-ID Laboratory (AIDL), USM and UiTM for supporting this work.


  1. 1.
    Letchuman, G. R., Nazaimoon, W. M. W., Mohamad, W. B. W., Chandran, L. R., Tee, G. H., Jamaiyah, H., et al. (2010). Prevalence of diabetes in the Malaysian National Health Morbidity Survey III 2006. Medical Journal of Malaysia, 65(3), 173–179.Google Scholar
  2. 2.
    Ho, B. K., Jasvindar, K., Gurpreet, K., Ambigga, D., Suthahar, A., Cheong, S. M., et al. (2014). Prevalence, awareness, treatment and control of diabetes mellitus among the elderly: The 2011 National Health and Morbidity Survey, Malaysia. Malaysian Fam Physician, 9(3), 12–19.Google Scholar
  3. 3.
    Bodenheimer, T., Wagner, E. H., & Grumbach, K. (2002). Improving primary care for patients with chronic illness. JAMA, 288(14), 1775–1779.CrossRefGoogle Scholar
  4. 4.
    Adler-Milstein, J., DesRoches, C. M., Furukawa, M. F., Worzala, C., Charles, D., Kralovec, P., et al. (2014). More than half of US Hospitals Have At Least a basic EHR, but stage 2 criteria remain challenging for most. Health Affairs (Millwood), 33(9), 1664–1671.CrossRefGoogle Scholar
  5. 5.
    Sheikh, A., Jha, A., Cresswell, K., Greaves, F., & Bates, D. W. (2014). Adoption of electronic health records in UK Hospitals: Lessons from the USA. Lancet, 384(9937), 8–9.CrossRefGoogle Scholar
  6. 6.
    Khalifa, M. (2014). Technical and human challenges of implementing hospital information systems in Saudi Arabia. Journal of Health Informatics in Developing Countries, 8(1), 12–25.Google Scholar
  7. 7.
    Inokuchi, R., Sato, H., Nakamura, K., Aoki, Y., Shinohara, K., Gunshin, M., et al. (2014). Motivations and barriers to implementing electronic health records and ED information systems in Japan. American Journal of Emergency Medicine, 32(7), 725–730.CrossRefGoogle Scholar
  8. 8.
    Latif, A. I., Othman, M., Suliman, A., & Daher, A. M. (2016). Current status, challenges and needs for pilgrim health record management sharing network, the case of Malaysia. International Archives of Medicine, 9(12), 1–10.Google Scholar
  9. 9.
    Adane, K., Muluye, D., & Abebe, M. (2013). Processing medical data: a systematic review”. Archives of Public Health, 71(1), 1–6.CrossRefGoogle Scholar
  10. 10.
    Carraro, P., & Plebani, M. (2009). Post-analytical errors with portable glucose meters in the hospital setting. Clinica Chimica Acta, 404(1), 65–67.CrossRefGoogle Scholar
  11. 11.
    Klonoff, D. C. (2014). Point-of-care blood glucose meter accuracy in the hospital setting. Diabetes Spectrum, 27(3), 174–179.CrossRefGoogle Scholar
  12. 12.
    Abdullah, S., Ismail, W., & Halim, Z. A. (2015). Implementation of wireless RFID for production line management system in a real environment. Wireless Personal Communication, 83(4), 3119–3132.CrossRefGoogle Scholar
  13. 13.
    Boonsong, W., & Ismail, W. (2014). Wireless monitoring of household electrical power meter using embedded RFID with wireless sensor network platform. International Journal of Distributed Sensor Networks, 10(6), 1–10.CrossRefGoogle Scholar
  14. 14.
    Chen, Y. -Y., Wu, Y. -T., Wu, C. -C., Wu, S. -M., & Jaw, F. -S. (2004). Development of wireless blood glucose meter and diabetes self-management system. In The 26th annual international conference of the IEEE engineering in medicine and biology society (Vol. 2, pp. 3384–3386).Google Scholar
  15. 15.
    Simpson, J. M., Cadio, M., Ramey, B. E., Tenbarge, J. D., Blackburn, M. J., Davies, R. G., et al. (2010). Methods and systems for wireless communication between a blood glucose meter and a portable communication device. US Patent 20100336145 A1.Google Scholar
  16. 16.
    Ow-Wing, K. M. (2013). Glucose monitoring system with wireless communications. US Patent 8372351. Google Scholar
  17. 17.
    Gammon, D., Arsand, E., Walseth, O. A., Andersson, N., Jenssen, M., & Taylor, T. (2005). Parent-child interaction using a mobile and wireless system for blood glucose monitoring. Journal of Medical Internet Research, 7(5), e57.CrossRefGoogle Scholar
  18. 18.
    Friman, A., Tresoldi, E., Kraft, U., Ebner, M., Engstorm, M., & Engstorm, F. (2010). Blood glucose meter capable of wireless communication. US Patent 20100228111 A1. Google Scholar
  19. 19.
    Shukla, R., Somani, S. B., & Shete, V. V. (2016). Wireless blood glucose monitoring system. In International conference on inventive computation technologies (pp. 1–4).Google Scholar
  20. 20.
    Adler, C. (2016). Systems and methods for transmitting glucose meter readings. US Patent 20160128571 A1.Google Scholar
  21. 21.
    Hodges, A., & Chatelier, R.(2002). Electrochemical method for measuring chemical reaction rates. US Patent 7022217 B2. Google Scholar
  22. 22.
    Pohanka, M., & Republic, C. (2008). Electrochemical biosensors—principles and applications. Methods, 6(2), 57–64.Google Scholar
  23. 23.
    Latha, N. A., Murthy, B. R., Madhav, K. V., Ramana, C. V. V., Clarke, W., & Kumar, V. S. (2011). Design and development of a microcontroller based system for the measurement of blood pressure. In 2011 International Conference on Recent Advanced Electrical and Electronic Control Engineering (Vol. 2(5), pp. 131–135).Google Scholar
  24. 24.
    Ismail, W., & Abdulla, R. (2012). Portable RFID reader for RLTS systems. PCT International Filing No: PCT/MY2011/000167, Country: Australia, Pub No: WO/2012/102600.Google Scholar
  25. 25.
    Tagsense (2010). RFID module users manual nano-UHF RFID reader. Retrieved March 19, 2017 from

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Auto-ID Laboratory (AIDL), School of Electrical and Electronics EngineeringUniversiti Sains Malaysia (USM)Nibong TebalMalaysia
  2. 2.Faculty of Electrical EngineeringUniversiti Teknologi MARAPermatang PauhMalaysia
  3. 3.Computing Department, Faculty of Art, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia

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