Literature DB >> 19735967

Strong corruption of electrocardiograms caused by cardiopulmonary resuscitation reduces efficiency of two-channel methods for removing motion artefacts in non-shockable rhythms.

Tobias Werther1, Andreas Klotz, Marcus Granegger, Michael Baubin, Hans G Feichtinger, Anton Amann, Hermann Gilly.   

Abstract

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.

Mesh:

Year:  2009        PMID: 19735967     DOI: 10.1016/j.resuscitation.2009.07.020

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  7 in total

1.  Sequential algorithm for life threatening cardiac pathologies detection based on mean signal strength and EMD functions.

Authors:  Emran M Abu Anas; Soo Y Lee; Md K Hasan
Journal:  Biomed Eng Online       Date:  2010-09-04       Impact factor: 2.819

2.  Removal of cardiopulmonary resuscitation artifacts with an enhanced adaptive filtering method: an experimental trial.

Authors:  Yushun Gong; Tao Yu; Bihua Chen; Mi He; Yongqin Li
Journal:  Biomed Res Int       Date:  2014-03-27       Impact factor: 3.411

3.  Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients.

Authors:  Mi He; Yubao Lu; Lei Zhang; Hehua Zhang; Yushun Gong; Yongqin Li
Journal:  PLoS One       Date:  2016-02-10       Impact factor: 3.240

4.  Reduction of CPR artifacts in the ventricular fibrillation ECG by coherent line removal.

Authors:  Anton Amann; Andreas Klotz; Thomas Niederklapfer; Alexander Kupferthaler; Tobias Werther; Marcus Granegger; Wolfgang Lederer; Michael Baubin; Werner Lingnau
Journal:  Biomed Eng Online       Date:  2010-01-06       Impact factor: 2.819

5.  Adult Basic Life Support: International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations.

Authors:  Theresa M Olasveengen; Mary E Mancini; Gavin D Perkins; Suzanne Avis; Steven Brooks; Maaret Castrén; Sung Phil Chung; Julie Considine; Keith Couper; Raffo Escalante; Tetsuo Hatanaka; Kevin K C Hung; Peter Kudenchuk; Swee Han Lim; Chika Nishiyama; Giuseppe Ristagno; Federico Semeraro; Christopher M Smith; Michael A Smyth; Christian Vaillancourt; Jerry P Nolan; Mary Fran Hazinski; Peter T Morley
Journal:  Resuscitation       Date:  2020-10-21       Impact factor: 5.262

Review 6.  Rhythm analysis during cardiopulmonary resuscitation: past, present, and future.

Authors:  Sofia Ruiz de Gauna; Unai Irusta; Jesus Ruiz; Unai Ayala; Elisabete Aramendi; Trygve Eftestøl
Journal:  Biomed Res Int       Date:  2014-01-09       Impact factor: 3.411

7.  A reliable method for rhythm analysis during cardiopulmonary resuscitation.

Authors:  U Ayala; U Irusta; J Ruiz; T Eftestøl; J Kramer-Johansen; F Alonso-Atienza; E Alonso; D González-Otero
Journal:  Biomed Res Int       Date:  2014-05-07       Impact factor: 3.411

  7 in total

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