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Sensor Abstraction for U-health Application Development: Filtering and Summarization for Accuracy Enhancement

유-헬스 앱 개발을 위한 센서 추상화: 정확도 향상을 위한 필터링 및 요약

  • Oh, Sam Kweon (School of Computer and Information Engineering, Hoseo University) ;
  • Lim, Eun Chong (School of Computer and Information Engineering, Hoseo University)
  • 오삼권 (호서대학교 컴퓨터정보공학부) ;
  • 임은총 (호서대학교 컴퓨터정보공학부)
  • Received : 2015.08.18
  • Accepted : 2015.10.08
  • Published : 2015.10.30

Abstract

Recently, researches on sensor-based U-health applications that provide personal health information such as blood pressure, body temperature, and glucose, have actively been studied. The health information obtained via sensors, however, may have accuracy problems so that they can not be used unprocessed. This paper proposes a sensor abstraction layer for enhancing the accuracy of sensor readings from biomedical sensors that interact with smart phones. This layer recognizes sensor types and converts sensor readings into a form as specified in ISO/IEEE 11073 Personal Health Standard. When necessary, not only a filtering method that eliminates outlier values from sensor readings but also a summarization method that transforms them into more suitable forms, can also be applied. An android-based development board is used for the evaluation of proposed sensor abstraction layer. The results obtained by applying filtering and summarization show improved accuracy over unprocessed sensor readings of the body temperature and heartbeat sensors.

최근 혈압, 체온 및 혈당 같은 개인 건강 정보를 알려주는 센서-기반의 유-헬스 앱에 대한 연구가 활발히 진행되고 있다. 그러나 센서들을 통해 얻어진 정보는 그 정확성에 문제가 있을 수 있으므로 가공되지 않은 상태로 사용하기 어려운 경우가 많다. 본 논문은 스마트폰과 연동하는 생체 센서들을 통해 얻어진 측정값들의 정확성을 향상시키기 위한 센서 추상화 계층을 제안한다. 이 계층은 연결된 센서의 종류를 인식하고 읽어온 센서 값들을 ISO/IEEE 11073 신체 건강 표준에 따라 변환하며, 필요한 경우 측정값들 중에서 이상치(outlier)를 제거하는 필터링(filtering) 기법과 구해진 값들을 보다 적합한 형태로 변환해주는 요약(summarization) 기법을 적용한다. 제안된 센서 추상화 계층의 평가를 위해 안드로이드 기반의 개발보드를 사용한다. 체온 센서와 심박 센서를 통해 얻어진 값들에 대해 필터링 및 요약 기법을 적용한 경우의 결과가 그렇지 않은 경우에 비해 향상된 정확성을 보인다.

Keywords

References

  1. T. G. Lee, "Smart healthcare and health-medical information system enforcement strategies," The Journal Korean Institute of Information Technology, Vol. 11, No. 1, pp.41-48, Jan. 2013.
  2. J. T. Park, S. M. Cheon, and S. J. Ko, "Trend on IOT-board healthcare service and platform," Information and Communications Magazine, Vol. 31, No. 12, pp.25-30, Dec. 2014
  3. W. S. Ahn, and J. T. Kim, "Blood glucose measurement principles of non-invasive blood glucose meter: focused on the detection methods of blood glucose," Journal of Biomedical Engineering Research, Vol. 33, No. 3, pp. 114-127, Sep. 2012. https://doi.org/10.9718/JBER.2012.33.3.114
  4. ISO/IEEE 11073-20601TM - Health informatics personal health device communication part 20601: application profile optimized exchange protocol [Internet]. Available: www.wikipedia.org/wiki/ISO/IEEE_11073.
  5. H. N. Park, S. H. Kim, and D. S. Yoo, "Present status and analysis for IEEE 11073 personal health device specializations," The Korean Institute of Communications and Information Sciences, Vol. 37, No. 6, pp.469-475, Jun. 2012. https://doi.org/10.7840/KICS.2012.37.6C.469
  6. S. B. Eun, S. S. So, and B. H. Kim, "A sensor node operation system supporting sensor abstractions for Ease development of USN applications," Korean Institute of Information Scientists and Engineers, Vol. 36, No. 5, pp.371-379, Oct. 2009.
  7. J. C. Nam, W. K. Seo, J. S. Bae, and Y. Z. Cho, "Design and development of personal healthcare system based on IEEE 11073/HL7 standards using smartphone," The Korean Institute of Communications and Information Sciences, Vol. 36, No. 12, pp.1556-1564, Dec. 2011. https://doi.org/10.7840/KICS.2011.36B.12.1556
  8. H. H. Do, J. M. In, and S. K. Lee, "Implementation of ASN.1 converter for applying ISO/IEEE 11073 MDER," Korean Institute of Information Technology, Vol. 10, No. 4, pp. 19-30, Apr. 2012.
  9. J. G. Pak, and K. H. Park, "Advanced pulse oximetry system for remote monitoring and management," Journal of Biomedicine and Biotechnology, Vol. 2012, No. 6, pp.1-8, Jun. 2012.
  10. D. K. Lee, G. H. Bang, S. J. Han, and D. J. Choi, "A design of U-health system on smart phone using ISO/IEEE 11073 PHD standard," in Proceedings of the 2nd World Congress on Computing and Information Technology (WCIT), KualaLumpur: Malaysia, pp.133-138, March, 2014.
  11. K. M. Kim, "Implementation of ISO/IEEE 11073-10404 monitoring system based on u-health service", Journal of Advanced Navigation Technology, Vol. 18, No. 6, pp.625-632, Dec. 2014. https://doi.org/10.12673/jant.2014.18.6.625
  12. M. Gupta, J. Gao, C. C. Aggarwal, and J. Han, "Outlier detection for temporal data: a survey," IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 1, pp.1-20, Sep. 2014. https://doi.org/10.1109/TKDE.2011.181
  13. D. Curone, G. M. Bertolotti, A. Cristiani, E. L. Secco, and G. Magenes, "A real-time and self-calibrating algorithm based on triaxial accelerometer signals for the detection of human posture and activity," IEEE Transactions on Information Technology in Biomedicine, Vol. 14, No. 4, pp. 1098-1105, July. 2010. https://doi.org/10.1109/TITB.2010.2050696
  14. I. B. Jung, and K. H. Kim, "A study of PPG wave and pulse measurement on radial artery using digital potentiometer and exponentially weighted moving average filter," The Korean Institute of Electrical Engineers, Vol. 63, No. 7, pp. 962-967, Jul. 2014 https://doi.org/10.5370/KIEE.2014.63.7.962