Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy
1
조회
0
다운로드
0
인용
0
참고문헌
초록
Abstract
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.
참고문헌 (11)
- "Resuscitation from ventricular fibrillation", 203, pp.255~260 (1968)
- "Pre-hospital cardiopulmonary resuscitation", 16, pp.2408~2412 (1985)
- "Pre-counter shock cardiopulmonary resuscitation improves ventricular fibrillation median frequency and myocardial readiness for successful defibrillation from prolonged ventricular fibrilla- tion, a randomized, controlled swine study", 40(6), pp.563~571 (2002)
- "Influence of cardiopulmonary resuscitation prior to defibrillation in patients with out-of-hospital ventricular fibrillation", 281(13), pp.1182~1188 (1999)
- "Electrocardio-graphic prediction of cardiopulmonary resuscitation success", 6(3), pp.192~195 (2000)
- "Electrocar- diographic prediction of the success of cardiac resuscitation", 27(4), pp.708~714 (1999)
- "Review article: analyzing the ventricular fibrillation waveform", 57, pp.11~20 (2003)
- "A computer package for extreme value and wave analysis, with reliability applications", 7, pp.125~148 (1993)
- "Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest", pp.1523~1529 (2000)
- "Neuro-Fuzzy Modeling and Control", 83, pp.378~390 (1995)
- "Fuzzy and Neural Approaches in Engineering", pp.194~205 (1997), John Wiley