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시-주파수 분석을 이용한 심실세동시 심전도 분석을 통한 제세동 예측에 관한 연구

Prediction of Defibrillation Success of Ventricular Fibrillation ECG Signals using Time-Frequency Analysis


The purpose of this study is to predict the defibrillation success of a ventricular Fibrillation ECG signal using time-frequency analysis. During CPR, coronary perfusion pressure and electrocardiogram were measured. Parameters extracted from time-frequency domain were served as predictor of resuscitation success. Time frequency distribution(TFD) of ECG signals was estimated from the smoothed pseudo Wigner-Ville distribution(SPWVD). Median frequency, peak frequency, 1/f slope, frequency band ratios$(2{\sim}4Hz,\;4{\sim}6Hz,\;6{\sim}8Hz,\;8{\sim}10Hz,\;10{\sim}12Hz,\;12{\sim}15Hz)$ were extracted from each TFD as function of time. Paired t-test was used to determine the differences in ROSC and non-ROSC groups. In the statistical results, we selected four significant parameters - median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. We made an attempt to predict defibrillation success by combining features extracted from time frequency distribution. Independent t-test was used to determine the differences ROSC and non-ROSC groups. Consequently, we selected four significant parameters-median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. The relationship between coronary perfusion pressure and ECG parameters was analyzed with linear regression analysis. R-square value was 55%. 1/f slope and $8{\sim}10Hz$ band ratio had the significant relationship with coronary perfusion pressure.

참고문헌 (15)

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  9. Stults, K. R., Brown, D. D., and Kerber, R. E., 'Ventricular Fibrillation Amplitude Predicts ability to Defibrillate', Journal of American College of Cardiology, vol. 9, pp. 152A, 1987 
  10. Dazell, G. W., and Adgey, A. A., 'Determinants of Successful Transthoracic Defi brillation and Outcome in Ventricular Fibrillation', British Heart Journal, vol. 65, pp. 311-316, 1991 
  11. Cohen, L., 'Time-Frequency Distributions - A Review', Proceeding of the IEEE, vol. 77, no. 7, pp. 941-981, 1989 
  12. Cohen, L., Time-Frequency Analysis, Prentice-Hall, 1995 
  13. Sattar, F., and Salomonsson, G., 'The Use of a Filter Bank and the Wigner-Ville Distributions for Time-Frequency Representation', IEEE Transaction On Signal Processing, vol. 48, no. 6, pp. 1776-1783, 1999 
  14. Hlawatch, F.,and Bounderzux-Bartes, G. F., 'Linear and Quadratic Time-Frequen cy Signal Representation', IEEE Signal Processing Magazine, pp. 21-67, Apr. 1992 
  15. Hlawatch, F., Manikam, T. G., Urbanke, R. L., and Jones, W., 'Smoothed pseudo -Wigner Distributions, Choi-Williams Distribution, and Cone-Kernel Franz Representation: Ambiguity-Domain Analysis and Experimental Comparison', Signal Processing, vol. 43, pp. 149-168, 1995 

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