Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest.

@article{Eftestol2000PredictingOO,
  title={Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest.},
  author={Trygve Eftestol and Kjetil Sunde and S Ole Aase and John. H. Husoy and Petter Andreas Steen},
  journal={Circulation},
  year={2000},
  volume={102 13},
  pages={1523-9}
}
BACKGROUND In 156 patients with out-of-hospital cardiac arrest of cardiac cause, we analyzed the ability of 4 spectral features of ventricular fibrillation before a total of 868 shocks to discriminate or not between segments that correspond to return of spontaneous circulation (ROSC). METHODS AND RESULTS Centroid frequency, peak power frequency, spectral flatness, and energy were studied. A second decorrelated feature set was generated with the coefficients of the principal component analysis… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 55 extracted citations

Wavelet-based markers of ventricular fibrillation in optimizing human cardiac resuscitation

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology • 2010
View 6 Excerpts
Highly Influenced

Ventricular defibrillation: Classification with G.E.M. and a roadmap for future investigations

2017 IEEE 56th Annual Conference on Decision and Control (CDC) • 2017
View 3 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 28 references

Spectral analysis of ventricular fibrillation and closed - chest cardiopulmonary

HU Strohmenger, KH Lindnder, IM Lindner
RESUSCITATION • 1996

Spectral analysis of ventricular fibrillation and closed-chest cardiopulmonary resuscitation

HU Strohmenger, KH Lindnder, IM Lindner
1996

Similar Papers

Loading similar papers…