A new shock advice algorithm designed to classify ECG signals during cardiopulmonary resuscitation

A shock advice algorithm (SAA) that reliably diagnoses the rhythm during cardiopulmonary resuscitation (CPR) would avoid unnecessary CPR interruptions and increase the probability of a successful resuscitation. Current approaches based on filtering the CPR artifact from the ECG or analyzing the corrupted ECG do not meet the American Heart Association´s (AHA) requirements for SAA. This study presents a preliminary design of a SAA to classify the rhythm during CPR. It is based on the analysis of five non-overlapping 3 s segments of the corrupt and the filtered ECG. A total of 290 non-shockable and 89 shockable records were analyzed and a specificity above the 95% AHA goal was obtained for a 89.5% sensitivity, only half a point below the AHA goal.