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KMID : 1137820060270020047
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의공학회지
2006 Volume.27 No. 2 p.47 ~ p.52
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Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy
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Shin Jae-Woo
Lee Hyun-Sook
Hwang Sung-Oh
Yoon Young-Ro
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Abstract
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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.
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KEYWORD
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ventricular fibrillation, defibrillation, adaptive neuro-fuzzy inference system, cardiopulmonary resuscitation
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