디지털융복합연구 (Journal of Digital Convergence)

  • 제12권4호
  • /
  • Pages.251-257
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  • 2014
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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M2M 기반 유헬스케어 데이터의 효율적인 전송 방안 연구

Research on a Method for Efficient u-Healthcare Data Transmission in M2M Environment

  • 조균연 (고려대학교 보건과학연구소)
  • 투고 : 2014.01.14
  • 심사 : 2014.04.20
  • 발행 : 2014.04.28
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⟨ 이전 논문 다음 논문 ⟩

초록

유헬스케어 환경에서는 M2M 기반에서 중요한 생체정보가 처리된다. M2M은 주로 무선네트워크를 기반으로 하는데, 무선네트워크는 제한된 대역폭과 낮은 신뢰성 등 극복해야할 과제가 많이 있다. 본 논문에서는 이 과제를 데이터 전송효율을 높여 해결하고자 하였으며, 생체정보에 대한 높은 압축특성을 갖는 uHLZW(u-Healthcare LZW) 압축 알고리즘을 제안하였다. 실험결과 기존의 압축알고리즘에 비해 1.6배에서 4배정도 압축효율이 개선됨을 알 수 있었다.

In u-Healthcare environment, large amounts of important vital information is processed through M2M(Machine to Machine). M2M is configured by wireless networks and has several problems for limited bandwidth and low reliability. Therefore, in this paper is proposed a method called uHLZW(u-Healthcare LZW) to improve channel efficiency to solve such problem. uHLZW algorithm has high compression ratio for vital data. The results showed that the average compression ratio of uHLZW got from 1.6 times to 4.0 times better than existing methods(Huffman and LZW compression).

키워드

참고문헌

  1. Lee SJ, Sim HJ, Lee AR, Lee TR. The Design of Maternity Monitoring System Using USN in Maternity Hospital. The Journal of Digital Policy & Management. 2013.
  2. Jung Hoon Park, Taegkeun Whangbo, IT convergence Healthcare technology, korea information and communications society. 2011.
  3. H. Mitsui, H. Kambe, H. Koizumi, Student Experiments for Learning Basic M2M Technologies by Implementing Sensor Networks System, in proc. ITHET 2010
  4. Wilde ET. Do emergency medical system response times matter for health outcomes? Health economics. 2013
  5. Cho GY, Lee SJ, Lee TR. Research on Enhancing Reliability of IT Convergence Technology Applied Emergency Management Information System. The Journal of Digital Policy & Management. 2013.
  6. M. Li, W. Lou, Data Security and Privacy in Wireless Body Area Networks, IEEE Wireless Communications, 2010
  7. A. Pantelopoulos, G. Ourbakis, A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis, IEEE Trans. On System, MAN and Cybernetics, 2010
  8. Seung-Man Chun, Jae-Wook Nah, Ki-Chan Lee, Jong-Tae Park, Policy-Bassed Emergency Bio Data Transmission Architecture for Smart Healthcare Service, Journal of the Institute of Electronic Engineers of Korea, 2011
  9. El-Masri S, Saddik B. An emergency system to improve ambulance dispatching, ambulance diversion and clinical handover communication-a proposed model. Journal of medical systems. 2012.
  10. Salomon D. A Consice Introduction to Data Compression: Springer; 2008.
  11. Blelloch G. Introduction to Data Compression, 2001.
  12. Galiano V, Lopez-Granado O, Malumbres MP, Migallon H. Fast 3D wavelet transform on multicore and many-core computing platforms. Journal of Supercomputing. 2013.
  13. Lee SJ, Roh YH, Kim YK, Lee TR. Geometric detection algorithm design for ECG data analysis using wavelet. International Journal of Bio-Science and Bio-Technology. 2013..
  14. Puthooran E, Anand RS, Mukherjee S. Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor. International Journal of Computational Intelligence Systems. 2013.
  15. Wikipedia article, "EEG, 뇌파, 뇌전도"
  16. Aswini Kumar, ECG-simplified, LifeHugger. 2010
  17. Wikipedia article, "Data Compression"
  18. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation. 2000.

피인용 문헌

  1. Design of U-healthcare System based on Smart-Cloth vol.9, pp.2, 2016, https://doi.org/10.17661/jkiiect.2016.9.2.237