Nonlinear energy operators for defibrillation shock outcome prediction

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.