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

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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A Evaluation Parameter Development of Anesthesia Depth in Each Anesthesia Steps by the Wavelet Transform of the Heart Rate Variability Signal

HRV 신호의 웨이브렛 변환에 의한 마취단계별 마취심도 평가 파라미터 개발

  • Jeon, Gye-Rok (Department of Biomedical Engineering, College of Medicine) ;
  • Kim, Myung-Chul (Dept. of Interdisciplinary Program in Biomedical Engineering. Graduate School, Pusan University) ;
  • Han, Bong-Hyo (Dept. of Interdisciplinary Program in Biomedical Engineering. Graduate School, Pusan University) ;
  • Ye, Soo-Yung (BK21 Medical Science Education Center, College of Medicine, Pusan University) ;
  • Ro, Jung-Hoon (Department of Biomedical Engineering, College of Medicine, Pusan University) ;
  • Baik, Seong-Wan (Department of Anesthesia and Pain Medicine, School of Medicine, Pusan University)
  • 전계록 (부산대학교 의학전문대학원 의공학교실) ;
  • 김명철 (부산대학교 의공학협동과정) ;
  • 한봉효 (부산대학교 의공학협동과정) ;
  • 예수영 (부산대학교 의학전문대학원 BK21 사업단) ;
  • 노정훈 (부산대학교병원 의공학과) ;
  • 백승완 (부산대학교 의학전문대학원 마취통증학교실)
  • Published : 2009.09.30
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Abstract

In this study, the parameter extraction for evaluation of the anesthesia depth in each anesthesia stages was conducted. An object of the this experiment study has studied 5 adult patients (mean $\pm$ SD age:$42{\pm}9.13$), ASA classification I and II, undergoing surgery of obstetrics and gynecology. Anaesthesia was maintained with Enflurane. HRV signal was created by R-peak detection algorithm form ECG signal. The HRV data were preprocessing algorithm. It has tried find out the anesthesia parameter which responds the anesthesia events and shows objective anesthesia depth according to anesthesia stage including pre-anesthesia, induction, maintenance, awake and post-anesthesia. In this study, proposed algorithm to analysis the HRV(heart rate variability) signal using wavelet transform in anesthesia stage. Three sorts of wavelet functions applied to PSD. In the result, all of the results were showed similarly. But experiment results of Daubeches 10 is better. Therefore, this parameter is the best parameter in the evaluation of anesthesia stage.

본 연구에서는 마취 단계에서 마취 심도 평가를 위한 파라미터 추출을 수행하였다. 연구대상은 평균 나이 $42{\pm}9.13$세, 신체등급 분류상 1 또는 2 등급에 속하는 산부인과 수술 환자를 선택하였다. 투약제로는 Enflurane으로 전신 마취를 시행하였다. HRV 신호는 ECG 신호로부터 R 피크치 검출 알고리즘에 의해 획득 되었다. HRV 데이터는 전처리 단계를 거쳤고, 마취 단계별 마취심도 평가 파라미터를 개발하기 위하여 마취단계를 마취 전, 마취유도, 수술중, 각성, 마취 후 등으로 구분하여 시행하였다. 본 연구에서는 마취단계에서 웨이브렛 변환을 이용한 HRV신호 분석 알고리듬이 제안되었다. 세 종류의 웨이브렛 함수를 적용한 PSD 분석 결과 마취 단계에 따라 모두 비슷한 양상을 나타내었으나, 이들 중 Daubeches 10의 실험 결과가 보다 양호하게 관측되어 마취 단계별 마취심도를 평가할 수 있는 특징 파라미터로서 가장 적절하다는 판단하였다.

Keywords

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