Abstract
Accurate prediction of shock success would avoid futile defibrillation attempts that may damage the myocardium, and would help optimizing treatment decisions for out-of-hospital cardiac arrest (OHCA) patients. This work applies the Smoothed Nonlinear Energy Operator (SNEO) to analyze the energy content of the pre-shock ventricular fibrillation (VF) waveform adquired by automated external defibrillators (AED). A database of 419 shocks was analyzed and shock outcome predictors were calculated in the a 5-s pre-shock ECG segment. The SNEO was compared to some classical VF features. For each feature a detector of successful shocks was designed minimizing the Balanced Error Rate (BER). Finally, using SNEO as shock outcome predictor the minimun pre-shock segment duration was determined. The SNEO has proven to be a good shock outcome predictor even for 2-s segments and it could be used to optimize treatment decisions for OHCA patients.
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