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Aim: We applied independent component analysis (ICA) to cardiopulmonary resuscitation (CPR)-corrupted human multichannel emergency ECGs with the aim of reconstructing the original ECGs., Materials: Two ICA algorithms (EFICA and JADE) were selected. Data for ICA were acquired by simultaneously recording eight ECG channels during CPR on a porcine model. The algorithms' reconstruction performance was assessed by the Spearman correlation coefficient (SCC) and the shock advice algorithm of an AED. We then compared the performance of EFICA with the established second-channel adaptive matching pursuit method (AF)., Results: ICA was applied to 918 corrupted ECG multichannel signals. The sensitivity of the AED's shock/no-shock decision increased from 93.5% (corrupted signal) to 99.5/99.8% (JADE/EFICA) in the selected independent component; specificity increased from 50.5% to 78.9/83.2% (JADE/EFICA). The SCCs comparing the reconstructed with the original signal (JADE: 0.75±0.15; EFICA: 0.76±0.15, n=918) were significantly higher than for the corrupted signal vs. the original (0.52±0.22). The SCC is significantly higher (p<0.01) using EFICA than AF (EFICA: 0.75±0.16; AF: 0.72±0.19, n=718). For all signals at all SNR levels, specificity did not differ significantly between EFICA (83.6%) and AF (80.2%). EFICA proved to be superior especially at low corruption levels (SNR<-5dB). Sensitivity was above 99.5% for both algorithms., Conclusion: We have demonstrated that CPR artefacts in the emergency ECG can be reduced using ICA. EFICA and JADE are at least as successful in this regard as are other published algorithms. In particular, non-shockable signals with low SNRs (<-5dB) are reconstructed significantly better (p=0.01) with EFICA than with AF., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Aim: For the analysis of ECG rhythms during ongoing CPR, single- or two-channel methods have been proposed to eliminate artefacts from the CPR-corrupted ECG. To refine, test and evaluate these algorithms with a realistic data set, we introduce an animal model with which we created an extended database of human ECGs with real CPR artefacts., Material and Methods: In a pig model real CPR-related artefacts were added to annotated human emergency ECGs. Via a special catheter placed in the oesophagus, ECG sequences (duration>10s) were fed in close to the dead pig's heart. The resulting surface potential was recorded on the thorax without and during ongoing chest compressions, which were monitored using a miniature force sensor., Results: The animals served as a vehicle for human ECGs, making it possible to create a database in which 918 real human ECG sequences (437 shockable and 481 non-shockable) were corrupted with CPR-induced artefacts. The achieved signal-to-noise ratios (SNR) ranged from -17 to +15 dB, sensitivity was 93.5% and specificity was 50.51%. The fed-in ECG and the uncorrupted surface ECG correlated almost perfectly (r=0.926+/-0.081; n=918), indicating negligible signal distortion due to the dead pig itself., Conclusion: As the generated database includes both the original and the corrupted ECG covering a wide range of SNRs as well as the compression force signal, it provides an extended data set to evaluate the reconstruction performance of CPR artefact-removal algorithms., (Copyright 2010 Elsevier Ireland Ltd. All rights reserved.)

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., Discussion: 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.

Aim: Cardiopulmonary resuscitation (CPR) artefact removal methods provide satisfactory results when the rhythm is shockable but fail on non-shockable rhythms. We investigated the influence of the corruption level on the performance of four different two-channel methods for CPR artefact removal., Materials and Methods: 395 artefact-free ECGs and 13 pure CPR artefacts with corresponding blood pressure readings as a reference channel were selected. Using a simplified additive data model we generated CPR-corrupted signals at different signal-to-noise ratio (SNR) levels from -10 to +10 dB. The algorithms were optimized on learning data with respect to SNR improvement and then applied to testing data. Sensitivity and specificity were derived from the shock/no-shock advice of an automated external defibrillator before CPR corruption and after artefact removal., Results: Sensitivity for the filtered data (>95%) was significantly superior to that for the unfiltered data (76%), p<0.001. However, specificity was similar for the filtered and unfiltered data (<90% vs 89.3%). For large artefacts (-10 dB) specificity decreased below 70%. No important difference in the performance of the four algorithms was found., Conclusion: Using a simplified data model we showed that, when the ECG rhythm is non-shockable, two-channel methods could not reduce CPR artefacts without affecting the rhythm analysis for shock recommendation. The reason could be poor reconstruction when the artefacts are large. However, poor reconstruction was not a hindrance to re-identifying shockable rhythms. Future investigations should both include the refinement of filter methods and also focus on reducing motion artefacts already at the recording stage.