Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy

  • Shin Jae-Woo (Department of Biomedical Engineering, Yonsei University) ;
  • Lee Hyun-Sook (Department of Korean Medicine Engineering, Sangji University) ;
  • Hwang Sung-Oh (Department of Emergency Medicine, Wonju College of Medicine) ;
  • Yoon Young-Ro (Department of Biomedical Engineering, Yonsei University)
  • Published : 2006.04.01
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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.

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References

  1. Redding, J. S. and Pearson, J. W., 'Resuscitation from ventricular fibrillation', Journal of the American Medical Association, Vol.203, pp.255-260, 1968 https://doi.org/10.1001/jama.203.4.255
  2. Richard, O. C. and Mickey, S. E., 'Pre-hospital cardiopulmonary resuscitation', Journal of the American Medical Association, Vol.16, pp.2408-2412, 1985
  3. Berg, R. A, Hilwig, R. W., Kern, K. B., and Ewy, G. A, 'Pre-counter shock cardiopulmonary resuscitation improvesventricular fibrillation median frequency and myocardial readiness for successful defibrillation from prolonged ventricular fibrillation, a randomized, controlled swine study', Annals of Emergency Medicine, Vol. 40, No. 6, pp.563-571, 2002 https://doi.org/10.1067/mem.2002.129866
  4. Cobb, L. A, Fahrenbruch, C. E., Walsh, T. R., Copass, M. K., Olsufka, M., Breskin, M., and Hallstrom, A P., 'Influence of cardiopulmonary resuscitation prior to defibrillation in patients with out-ofhospital ventricular fibrillation', The Journal of the American Medical Association, Vol. 281, No. 13, pp.1182-1188, 1999 https://doi.org/10.1001/jama.281.13.1182
  5. Strohmenger, H. U. and Volker, W., 'Electrocardio-graphic prediction of cardiopulmonary resuscitation success', Current Opinion in Critical Care, Vol. 6, No.3, pp.192-195,.2000 https://doi.org/10.1097/00075198-200006000-00009
  6. Noc, M., Harry, W. M., Pernat, T. W., and Bisera, J., 'Electrocardiographic prediction of the success of cardiac resuscitation', Critical Care Medicine, Vol. 27, No.4, pp.708-714, 1999 https://doi.org/10.1097/00003246-199904000-00021
  7. Reed, M. J., Clegg, G. R., and Robertson, C. E., 'Review article: analyzing the ventricular fibrillation waveform', Resuscitation, Vol. 57, pp.11-20, 2003 https://doi.org/10.1016/S0300-9572(02)00441-0
  8. Rychlik I. and Lindgren, G., 'A computer package for extreme value and wave analysis, with reliability applications', Probability in the Eng. and lnf. Sci., Vol. 7, pp.125-148, 1993 https://doi.org/10.1017/S0269964800002825
  9. Efetstol, T., Sunde, K., Ases, S. O., Husoy, J. H, and Steen, P.A., 'Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest'. Circulation, September 26, pp.1523-1529, 2000
  10. Jang R. and Sun, C-T., 'Neuro-Fuzzy Modeling and Control', Proceeding of IEEE, Vol. 83, pp.378-390, 1995
  11. Hines, J. W., Fuzzy and Neural Approaches in Engineering, Florida: John Wiley, pp.194-205, 1997