Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Detrended Fluctuation Analysis of EEG on a Depth of Anestheisa

뇌파신호의 DFA 분석을 이용한 마취심도 측정

  • Ye, Soo Young (Department of Mechatronics Engineering, Division of Information systems Engineering) ;
  • Baek, Seung-Wan (Department of Anesthesia and Pain Medicine, School of Medicine, Pusan University)
  • 예수영 (동서대학교 정보시스템공학부 메카트로닉스공학과) ;
  • 백승완 (부산대학교 의학전문대학원 마취통증학교실)
  • Received : 2010.04.22
  • Accepted : 2010.07.06
  • Published : 2010.07.31
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Abstract

The DFA(detrended fluctuation analysis) which is included the correlation property of the EEG is used to analysis the depth of anesthesia. We studied ASA I or II adult patients supported by the society of anesthesiologists. Patients with history of dementia and neurological disorder are excluded. Average age is $48.9{\pm}10.9$ old, average weight is $57.1{\pm}8.2$ kg and average hight is $158{\pm}6.6$cm of the patients under the operation. Anesthesia medicine is Sevoflurane and the stages of anesthesia are 6 stages, that is pre-operation, induction, right after induction, stop the medicine and post-operation. Among the scaling exponent ${\alpha}1$, ${\alpha}2$, ${\alpha}3$ we know that ${\alpha}1$, ${\alpha}3$, were well appeared to discriminate pre-operation, induction, right after induction, stop the medicine and post-operation. So we confirmed that the parameters is useful to the depth of anesthesia.

EEG 신호에 내포된 상관특성을 알 수 있는 스케일 분석 기법인 DFA를 이용하여 수술 중 마취심도를 분석하고자하였다. 마취과 학회에서 제공하는 신체 분류 등급 1(건강한 환자), 2(경한 전신 질환, 기능 제한 없음) 등급의 환자를 대상으로 하였다. 정신병력이나 신경계 이상이 있는 환자는 제외하였다. 수술 중 마취 환자의 평균 연령은 $48.9{\pm}10.9$ 세이고, 평균체중은 $57.1{\pm}8.2$ kg, 평균 신장은 $158{\pm}6.6$cm 였다. 수술을 위한 마취 약제로는 Sevoflurane를 사용하였고, 수술단계는 수술전, 마취유도, 마취유도 직후, 수술중, 마취제 중지, 수술 후의 6단계로 나누어 분석하였다. DFA의 ��${\alpha}1$, ${\alpha}2$, ${\alpha}3$ 중 ${\alpha}1$, ${\alpha}3$는 수술전단계, 마취 유도 단계, 마취 유도 단계 직후, 마취제 중지 단계, 수술후 단계를 구별 할 수 있는 파라미터들로 수술 중 마취 심도를 평가 할 수 있는 파라미터로 이용될 수 있음을 확인 하였다.

Keywords

References

  1. Ghoneim, MM, Block RI, "Learning and Memory during general anestheisa", Aneshtesiology, vol. 87, pp. 387-410, 1997. https://doi.org/10.1097/00000542-199708000-00027
  2. Jones JG, "Perception and memory during general anesthesia", Br J Anesth, vol. 73, pp. 31-37, 1994. https://doi.org/10.1093/bja/73.1.31
  3. H. L. Kaul, and Neerja Bharti, "Monitoring depth of Anesthesia,'' Indian J. Anaesth. vol.46, no.4, pp. 323-332, 2002.
  4. Faulconer A Jr, Pender JW, Bickford RG. "The influence of partial pressure of nitrous oxide on the depth of anesthesia and the electro-encephalogram in man", Anesthesiology, vol 10, pp. 601-606, 1949. https://doi.org/10.1097/00000542-194909000-00010
  5. Drummond JC, Brann CH, Perkins DE, Wolfe DE, "A comparison of median frequency, spectral edge frequency, a frequency band power ratio, total power, and dominance shift in the determination of depth of anesthesia", Acta Anesthesiol Scand, vol. 35, pp. 693-699, 1991. https://doi.org/10.1111/j.1399-6576.1991.tb03374.x
  6. 전계록, 김명철, 한봉효, 예수영, 노정훈, 백승완, "HRV 신호의 웨이브렛 변환에 의한 마취단계별 마취심도평가 파라미터 개발", 한국산학기술학회논문지, 제10권, 제9호, pp. 2460-2470, 9월, 2009. https://doi.org/10.5762/KAIS.2009.10.9.2460
  7. 예수영, 백승완, 김재형, 박준모, 전계록, "뇌파스펙트럼 분석에 의한 마취심도지표개발", 대한의용생체공학회, 제30권, 제4, pp. 327-332, 8월, 2009.
  8. 박종덕, 예수영, 전계록, 허영, "The estimation of the depth od anesthetic using higher-order spectrum analysis of EEG signals", 대한의용생체공학회, 제28권, 제2호, pp. 287-293, 4월, 2007년.
  9. E. Wodey, O. Tirel, J. Y. Bansard, A. Terrier, C. Chanavaz, R. Harris, C. Ecoffey and L. Senhadji, "Impact of age on both BIS values and EEG bispectrum during anaesthesia with sevoflurane in children", British Journal of Anaesthesia, vol. 94, no. 6, pp.810-820, 2005. https://doi.org/10.1093/bja/aei140
  10. P. Hans, P. Y. Dewandre, J. F. Brichant and V. Bonhomme, "Effects of nitrous oxide on Spectral Entropy of the EEG during surgery under balanced anaesthesia with sufentanil and sevoflurane", Acta Anaesth. Belg., vol. 56, pp. 37-43, 2005.
  11. H.L. Kaul, Neerjaz Bharti, "Monitoring depth of anesthesia", Indian J. Anaesth. vol.46, no. 4, pp. 323-332, 2002.
  12. Jun-Seok Lee, Byung-Hwan Yang, Jang-Han Lee, Jun-Ho Choi, Ihn-Geun Choi, Sae-Byul Kim, "Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls", Clinical Neurophysiology, vol. 118, Issue 11, pp. 2489-2496, 2007. https://doi.org/10.1016/j.clinph.2007.08.001
  13. C.K. Peng, Shlomo Havlin, H. Eugene Stanley, Ary L. Goldgerger, "Quantification of scaling exponents and corssover phenomena in nonstationary heartbeat time series", Chaos, vol. 5, no. 1, pp. 82-87, 1995. https://doi.org/10.1063/1.166141
  14. M. Jospin, P. Caminal, E. W. Jensen, H. Litvan, M. Vallverdu, M. M. R. F. Struys, H. E. M. Vereecke, and Daniel T. Kaplan, "Detrended Fluctuation Analysis of EEG as a Measure of Depth of Anesthesia", IEEE Transactions on Biomedical medical engineering, vol. 54, no. 5, may, 2007.
  15. X. Zhang, R. J.Roy, E. Weber Jensen, "EEG Complexity as a Measure of Depth of Aneshtesia for Patients", IEEE Transactions on Biomedical medical engineering, vol. 48, no. Dec., 2001.
  16. T. Nishiyama, T. Mausutawa, K. Hanaoka, "A Comparison of the Clinical Usefulness of Three Different Electroencephalogram Monitors: Bispectral Index, Processed Electroencephalogram, and Alaris Auditory Evoked Potentials", International Anesthesia Research Society, vol.98, pp. 1341-1345, 2004.