Removing piston-driven mechanical chest compression artefacts from the ECG

Piston-driven mechanical chest compression (CC) devices induce a quasi-periodic artefact in the ECG, making rhythm diagnosis unreliable. Data from 230 out-of-hospital cardiac arrest (OHCA) patients were collected in which CCs were delivered using the piston driven LUCAS-2 device. Underlying rhythms were annotated by expert reviewers in artefact-free intervals. Two artefact removal methods (filters) were introduced: a static solution based on Goertzel's algorithm, and an adaptive solution based on a Recursive Least Squares (RLS) filter. The filtered ECG was diagnosed by a shock/no-shock decision algorithm used in a commercial defibrillator and compared with the rhythm annotations. Filter performance was evaluated in terms of balanced accuracy (BAC), the mean of sensitivity (shockable) and specificity (nonshockable). Compared to the unfiltered signal, the static filter increased BAC by 20 points, and the RLS filter by 25 points. Adaptive filtering results in 99.0% sensitivity and 87.3% specificity.

[1]  T. Eftestøl,et al.  Fully automatic rhythm analysis during chest compression pauses. , 2015, Resuscitation.

[2]  P. Steen,et al.  Effects of Interrupting Precordial Compressions on the Calculated Probability of Defibrillation Success During Out-of-Hospital Cardiac Arrest , 2002, Circulation.

[3]  Rabab Kreidieh Ward,et al.  Fast RLS Fourier analyzers capable of accommodating frequency mismatch , 2007, Signal Process..

[4]  T. Eftestøl,et al.  Feasibility of automated rhythm assessment in chest compression pauses during cardiopulmonary resuscitation. , 2013, Resuscitation.

[5]  Pavel Rajmic,et al.  Goertzel algorithm generalized to non-integer multiples of fundamental frequency , 2012, EURASIP J. Adv. Signal Process..

[6]  Peng Gao,et al.  An Enhanced Adaptive Filtering Method for Suppressing Cardiopulmonary Resuscitation Artifact , 2017, IEEE Transactions on Biomedical Engineering.

[7]  J. Soar,et al.  Adult basic life support and automated external defibrillation , 2015 .

[8]  Maaret Castrén,et al.  European Resuscitation Council Guidelines for Resuscitation 2010 Section 2. Adult basic life support and use of automated external defibrillators , 2010, Resuscitation.

[9]  T. Eftestøl,et al.  Filtering mechanical chest compression artefacts from out-of-hospital cardiac arrest data. , 2016, Resuscitation.

[10]  Trygve Eftestøl,et al.  A Least Mean-Square Filter for the Estimation of the Cardiopulmonary Resuscitation Artifact Based on the Frequency of the Compressions , 2009, IEEE Transactions on Biomedical Engineering.

[11]  Sofía Ruiz de Gauna,et al.  A high-temporal resolution algorithm to discriminate shockable from nonshockable rhythms in adults and children. , 2012, Resuscitation.