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Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy
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  • Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy
  • Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy
저자명
Shin. Jae-Woo,Lee. Hyun-Sook,Hwang. Sung-Oh,Yoon. Young-Ro
간행물명
Journal of biomedical engineering research : the official journal of the Korean Society of Medical & Biological Engineering
권/호정보
2006년|27권 2호|pp.47-52 (6 pages)
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대한의용생체공학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The purpose of this study was to predict successful defibrillation in ventricular fibrillation using parameters extracted by wave analysis method and neuro-fuzzy. Total 15 dogs were tested for predicting successful defibrillation. Feature parameters were extracted for return of spontaneous circulation (ROSC) and non-ROSC by wave analysis method, and these parameters are an irregularity factor, spectral moments, mean power of level-crossing spectrum, and mean of alpha-significant value. Additionally, two parameters by analyzing method of frequency were extracted into a mean of power spectrum and a mean frequency. Then extracted parameters were analyzed in which parameters result to have high performance of discriminating ROSC and non-ROSC by a statistical method of t-test. The average of sensitivity and specificity were 62.5% and 75.0%, respectively. The average of positive predictive factor and negative predictive factor were 61.2% and 75.8%, respectively.