A least mean-square filter using compression frequency to remove CPR artifacts achieved a sensitivity above 95% and specificity above 85% for AED shock advice during sudden cardiac arrest.
Does an LMS filter based on compression frequency accurately remove CPR artifacts to allow reliable AED rhythm analysis during compressions?
An LMS filter using compression frequency can accurately model and remove CPR artifacts from ECGs, potentially allowing uninterrupted chest compressions during AED rhythm analysis.
Cardiopulmonary resuscitation (CPR) artifacts caused by chest compressions and ventilations interfere with the rhythm diagnosis of automated external defibrillators (AED). CPR must be interrupted for a reliable diagnosis. However, pauses in chest compressions compromise the defibrillation success rate and reduce perfusion of vital organs. The removal of the CPR artifacts would enable compressions to continue during AED rhythm analysis, thereby increasing the likelihood of resuscitation success. We have estimated the CPR artifact using only the frequency of the compressions as additional information to model it. Our model of the artifact is adaptively estimated using a least mean-square (LMS) filter. It was tested on 89 shockable and 292 nonshockable ECG samples from real out-of-hospital sudden cardiac arrest episodes. We evaluated the results using the shock advice algorithm of a commercial AED. The sensitivity and specificity were above 95% and 85%, respectively, for a wide range of working conditions of the LMS filter. Our results show that the CPR artifact can be accurately modeled using only the frequency of the compressions. These can be easily registered after small changes in the hardware of the CPR compression pads.
Irusta et al. (Fri,) conducted a other in Out-of-hospital sudden cardiac arrest (n=381). Least mean-square (LMS) filter was evaluated on Sensitivity and specificity of the shock advice algorithm. A least mean-square filter using compression frequency to remove CPR artifacts achieved a sensitivity above 95% and specificity above 85% for AED shock advice during sudden cardiac arrest.