The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Comparative Study of Compression Methods and the Development of CODEC Program of Biological Signal for Emergency Telemedicine Service

응급 원격 진료 서비스를 위한 생체신호 압축 방법 비교 연구 및 압축/복원 프로그램 개발

  • Published : 2003.05.01
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Abstract

In an emergency telemedicine system such as the High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2)$ of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity, it is also necessary to compress the biological data besides other multimedia data. For this purpose, we investigate and compare the ECG compression techniques in the time domain and in the wavelet transform domain, and present an effective lossless compression method of the biological signals using PEG Huffman table for an emergency telemedicine system. And, for the HMRET service, we developed the lossless compression and reconstruction program or the biological signals in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

Keywords

References

  1. 고품질 멀티미디어 기반 응급 원격진료 서비스. 정보통신부 차세대 인터넷 응용사업과제 지원사업 과제 제안서. 연세대학교 Jan. 2001
  2. The MIT-BIH ECG data base. available from the Harvard-MIT Division of Health Sciences and Technology, 1992
  3. U.E. Ruttimann and HV. Pipberger,'Compression of ECG by prediction or interpolation and entropy encoding,' IEEE Trans. on BME Vol. 26, No. 11, pp. 613-623, Nov. 1979 https://doi.org/10.1109/TBME.1979.326543
  4. S. M. S. Jalaleddine, et al, 'ECG data compression-techniques-A unified approach,' IEEE Trans. onBME, Vol. 37, No. 4, pp.329-343, April 1990 https://doi.org/10.1109/10.52340
  5. W. J. Tompkins, Biomedical Digital Signal Processing, Prentice-Hall, 1993
  6. W.J. Tompkins Eds., Design of Microcomputer-Based Medical Instrumentation, Prentice-Hall, 1981
  7. N.S. Jayant, Digital Coding of Waveforms,Prentice-Hall, 1984
  8. T.J. Lynch, Data Compression, LLP , 1985
  9. P.E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987
  10. K. Sayood, Introduction to Data Compression, 2nd. Ed., Morgan Kaufmann, 2000
  11. 이문호, C언어 영상 통신의 신호처리, 대영사, 1999
  12. 황재정, 디지털 영상공학, 도서출판 아진, 1999
  13. S.C.Tai, 'Designing ECG sub-band coders,' Medical & Biological Engineering & Computing,pp.643-647, Nov. 1993 https://doi.org/10.1007/BF02441816
  14. J. Chen and S. Itoh, 'A Wavelet Transform-Based ECG Compression Method Guaranteeing desiredSignal Quality,' IEEE Trans. on BME, pp.1414-1419, Vol.45, No. 12, Dec. 1998 https://doi.org/10.1109/10.730435
  15. R.M. Rao and A.S. Bopardikar, Wavelet Transforms Introduction to Theory and Applications, Addison Wesley, 1998