During cardiopulmonary resuscitation, excessive ventilation rates decrease cardiac output, thus reducing the chance of survival. We have developed a simple method to automatically detect ventilations based on the analysis of the thoracic impedance signal recorded through defibrillation pads. We used 18 out-of hospital cardiac arrest episodes that contained both ventilations provided during chest compressions (CCs) and during pauses in CCs. The detection algorithm first identified fluctuations on the preprocessed impedance signal. Then, it characterized the fluctuations by features for amplitude, duration and slope. Finally, a decision system based on static and dynamic thresholds was applied in order to determine whether each fluctuation corresponded to a ventilation. Sensitivity (Se) and positive predictive value (PPV) for the test set (2831 ventilations) were 97% and 94%, respectively. Before intubation (343 ventilations), Se and PPV were 92% and 79%, and 97% and 97% after intubation. The performance was very similar for intervals with and without CCs. The proposed method could be implemented in automatic external defibrillators for ventilation rate monitoring.
展开▼
