EEG Signal Characteristic Analysis for Monitoring of Anesthesia Depth Using Bicoherence Analysis Method

바이코히어런스 분석 기법을 이용한 마취 단계별 뇌파의 특성 분석

  • 박준모 (부산대학교 의과대학 의공학교실) ;
  • 박종덕 (한국전기연구원 융합기술연구단) ;
  • 전계록 (부산대학교 의과대학 의공학교실) ;
  • 허영 (한국전기연구원 융합기술연구단)
  • Published : 2006.01.01

Abstract

Although reachers have studied for a long time, they don't make criteria for anesthesia depth. anesthetists can't make a prediction about patient's reaction. Therefor, patients have potential risk such as poisonous side effect late-awake, early-awake and strain reaction. EEG are received from twenty-five patients who agreed to investigate themselves during operation with Enflurane-anesthesis in progress of anesthesia. EEG are divided pre-anesthesia, before incision of skin, operation 1, operation 2, awaking, post-anesthesia by anesthesia progress step. EEG is applied pre-processing, base line correct, linear detrend to get more reliable data. EEG data are handled by electronic processing and the EEG data are calculated by bicoherence. During pre-anesthesia and post anesthesia, appearance rate of bicoherence value is observed strong appearance rate in high frequency range($15\~30Hz$). During the anesthesia of patient, a strong appearance rate is revealed the low frequency area(0~10Hz). After bicoherence is calculated by percentage of a appearance rate, that is, Bicpara$\#$1, Bicpara$\#$2, Bicpara$\#$3 and Bicpara$\#$4 parameter are extracted. In result of bicoherence analysis, Bicpara$\#$2 and Bicpara#4 are considered that the best parameter showed progress of anesthesia effectively. And each separated bicoherence are calculated by average bicoherence's numerical value, divide by 2 area, appear by each BicHz$\#$1, BicHz$\#$2, and observed BicHz$\#$1/BicHz$\#$2's change. In result of bicoherence analysis, BicHz$\#$1, BicHz$\#$2 and BicHz$\#$1/BicHz$\#$2 are considered that the best parameter showed progress of anesthesia effectively. In conclusion, I confirmed the anesthesia progress phase, concluded to usefulness of parameter on bispectrum and bicoherence analysis and evaluated the depth of anesthesia. In the future, it is going to use for doctor's diagnosis and apply to protect an medical accident owing to anesthesia.

Keywords

References

  1. 대한마취과학회 교과서 편집위원회, 마취과학, 여문각, pp. 1-9, 2002
  2. Stanski D. R, 'Monitoring depth of anesthesia.' In Miller RD (eds): Anesthesia. Philadelphia, Churchill Livingstone, 1900: pp. 85-102
  3. Pres-Robert C, 'Anaesthesia: A practical construct.' Br J Anaesth 1987; 59: pp. 1341-5 https://doi.org/10.1093/bja/59.11.1341
  4. Sebel PS, 'Evaluation of anaesthetic depth', Br J Hosp Med 1987; 38: pp. 116-7
  5. Chiappa K. H, Rapper AH, 'Evoked potentials in clinical medicine(second of two parts)', NEJM, 1982 b;306; pp. 1205-11 https://doi.org/10.1056/NEJM198205203062004
  6. 백운이, 'Application of EEG assessment on anesthetic depth', 대한뇌신경마취연구회학회지, 제6권, 제01호, 2001
  7. Joas T A, Stevens WC, Eger El II, 'Electroencephalographic seizures in dogs during anesthesia', Br J Aneath, 1971, 43 : pp. 739-745 https://doi.org/10.1093/bja/43.8.739
  8. Hagihira S, Takashina M, Mori T, Mashimo T, Yoshiya I. ,'Practical issues in bispectral analysis of electroencephalographic signals.', Anesth Analg. 2001 Oct;93(4): pp. 966-70 https://doi.org/10.1097/00000539-200110000-00032
  9. Sigl JC, Chamoun NC, 'An introduction to bispectral analysis for the EEG', J Clin Monit., 10: pp. 392-404, 1994 https://doi.org/10.1007/BF01618421
  10. 백승완, 이승진, 박준모, 김재현, 박철한, 남기곤, 노정훈, 전계록, 'Bispectrum 분석을 이용한 마취심도의 측정에 관한 연구', 대한마취과학회지, Vol 46, No 2, pp. 139-144, 2004
  11. Richard C. Watt, Chris Sisemore, Ansel Knsel Kaneoto, J. Scott Polson 'Bicoherence of EEG can be used to differentiate anesthetic levels', 18th Annual International Conference of IEEE, 1996 https://doi.org/10.1109/IEMBS.1996.646415
  12. T. H. Bullock, J. Z, Achimowicz, R.B. Duckrow, S.S. Spencer, V.J. Iragui-Madoz, 'Bicoherence of intracranial EEG in sleep, wakefulness and seizures', Electroencephalography and clinical Neurophysiology 103, pp. 661-678, 1997 https://doi.org/10.1016/S0013-4694(97)00087-4
  13. Jong duk Park, Young Huh, Jun Mo Park, Gye rok Jeon, 'A Study on the EEG Signal Characteristic Using High Order Spectrum Analysis Method', ITC-CSCC 2005. 7
  14. Mysore R. Raghuveer, Chrysostomos L. Nikias, 'Bispectrum Estimation: A Parametric Approach', IEEE Transactions on acoustics, SPEECH AND SIGNAL PROCESSING, Vol ASSP-33, NO.4, October 1985 https://doi.org/10.1109/TASSP.1985.1164679