Automated Algorithm for QRS Detection in Cardiac Arrest Patients with PEA

Abstract

Pulseless electrical activity (PEA) is one of the most common rhythms during a cardiac arrest (CA), and it consists in lack of palpable pulse in presence of electrical activity in the heart. The main treatment for a CA is the cardiopulmonary resuscitation (CPR), including chest compressions and ventilations, together with defibrillation shocks and drugs when necessary. The therapy of PEA depends on its characteristics, mainly the morphology of the QRS complex. Well known algorithms for QRS complex detection and delineation were designed for hemo-dynamically stable patients with pulsed rhythm (PR). The aim of this study was to develop an automatic method for QRS complex detection in patients with PEA during CA. The database for this study consists of 5128 PEA segments from 264 in-hospital CA patients. The ECG signal was decomposed using the stationary wavelet transform, a peak detector was applied on the third detail component and a multicomponent verification was set to detect the peaks. Finally, a time alignment of the detected QRS complexes was performed using the original ECG signal. The proposed method presents median (IQR) Se/PPV/F1 values of 92.4(15.2)/88.5(15.4)/88.8(15.6) for PEA segments.