title: Reduction of CPR artifacts in the ventricular fibrillation ECG by coherent line removal.
abstract: BACKGROUND
  Interruption of cardiopulmonary resuscitation (CPR) impairs the perfusion of the fibrillating heart, worsening the chance for successful defibrillation. Therefore ECG-analysis during ongoing chest compression could provide a considerable progress in comparison with standard analysis techniques working only during "hands-off" intervals.
  
  
  METHODS
  For the reduction of CPR-related artifacts in ventricular fibrillation ECG we use a localized version of the coherent line removal algorithm developed by Sintes and Schutz. This method can be used for removal of periodic signals with sufficiently coupled harmonics, and can be adapted to specific situations by optimal choice of its parameters (e.g., the number of harmonics considered for analysis and reconstruction). Our testing was done with 14 different human ventricular fibrillation (VF) ECGs, whose fibrillation band lies in a frequency range of [1 Hz, 5 Hz]. The VF-ECGs were mixed with 12 different ECG-CPR-artifacts recorded in an animal experiment during asystole. The length of each of the ECG-data was chosen to be 20 sec, and testing was done for all 168 = 14 x 12 pairs of data. VF-to-CPR ratio was chosen as -20 dB, -15 dB, -10 dB, -5 dB, 0 dB, 5 dB and 10 dB. Here -20 dB corresponds to the highest level of CPR-artifacts.
  
  
  RESULTS
  For non-optimized coherent line removal based on signals with a VF-to-CPR ratio of -20 dB, -15 dB, -10 dB, -5 dB and 0 dB, the signal-to-noise gains (SNR-gains) were 9.3 +/- 2.4 dB, 9.4 +/- 2.4 dB, 9.5 +/- 2.5 dB, 9.3 +/- 2.5 dB and 8.0 +/- 2.7 (mean +/- std, n = 168), respectively. Characteristically, an original VF-to-CPR ratio of -10 dB, corresponds to a variance ratio var(VF):var(CPR) = 1:10. An improvement by 9.5 dB results in a restored VF-to-CPR ratio of -0.5 dB, corresponding to a variance ratio var(VF):var(CPR) = 1:1.1, the variance of the CPR in the signal being reduced by a factor of 8.9.
  
  
  CONCLUSIONS
  The localized coherent line removal algorithm uses the information of a single ECG channel. In contrast to multi-channel algorithms, no additional information such as thorax impedance, blood pressure, or pressure exerted on the sternum during CPR is required. Predictors of defibrillation success such as mean and median frequency of VF-ECGs containing CPR-artifacts are prone to being governed by the harmonics of the artifacts. Reduction of CPR-artifacts is therefore necessary for determining reliable values for estimators of defibrillation success.
  
  
  CONCLUSIONS
  The localized coherent line removal algorithm reduces CPR-artifacts in VF-ECG, but does not eliminate them. Our SNR-improvements are in the same range as offered by multichannel methods of Rheinberger et al., Husoy et al. and Aase et al. The latter two authors dealt with different ventricular rhythms (VF and VT), whereas here we dealt with VF, only. Additional developments are necessary before the algorithm can be tested in real CPR situations.
authors.affiliation: University Clinic of Anesthesia, Innsbruck Medical University, Anichstr 35, A-6020 Innsbruck, Austria. anton.amann@i-med.ac.at
authors.forename: Anton
authors.initials: A
authors.lastname: Amann
authors.forename: Andreas
authors.initials: A
authors.lastname: Klotz
authors.forename: Thomas
authors.initials: T
authors.lastname: Niederklapfer
authors.forename: Alexander
authors.initials: A
authors.lastname: Kupferthaler
authors.forename: Tobias
authors.initials: T
authors.lastname: Werther
authors.forename: Marcus
authors.initials: M
authors.lastname: Granegger
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Lederer
authors.forename: Michael
authors.initials: M
authors.lastname: Baubin
authors.forename: Werner
authors.initials: W
authors.lastname: Lingnau
mesh_terms: D000465:Algorithms; D000818:Animals; D016477:Artifacts; D016887:Cardiopulmonary Resuscitation / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005583:Fourier Analysis; D006801:Humans; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes; D013552:Swine; D014693:Ventricular Fibrillation / Q000503:physiopathology