Literature DB >> 15135189

Feasibility of shock advice analysis during CPR through removal of CPR artefacts from the human ECG.

Joar Eilevstjønn1, Trygve Eftestøl, Sven Ole Aase, Helge Myklebust, John Håkon Husøy, Petter Andreas Steen.   

Abstract

Mechanical activity from chest compressions and ventilations during cardiopulmonary resuscitation (CPR) introduces artefact components into the electrocardiogram (ECG). CPR must therefore be discontinued for reliable shock advice analysis in automated external defibrillators. Reducing or eliminating this detrimental "hands-off" time by removing the CPR artefacts, should significantly improve the defibrillation success rate. The feasibility of this was tested by removing the CPR artefacts using a multichannel adaptive filter, the multichannel recursive adaptive matching pursuit (MC-RAMP) algorithm. Human ECG and reference channel data from episodes with both shockable and non-shockable underlying heart rhythms were recorded from 105 patients with out-of-hospital cardiac arrest. The performance of a shock advice algorithm was evaluated before and after artefact removal using the MC-RAMP algorithm. From a test set consisting of 92 shockable and 174 non-shockable episodes a sensitivity of 96.7% and specificity of 79.9% was achieved, an increase of approximately 15 and 13%, respectively, compared to no filtering. Good sensitivity was achieved, enabling ECG analysis during CPR that would reduce the hands-off time on patients with shockable rhythms. However, CPR artefact removal on non-shockable rhythms proved a more difficult problem. We need a better understanding of the physiological mixing of artefacts and the underlying heart rhythm and suggest clinical trials to investigate the nature of CPR artefacts further.

Entities:  

Mesh:

Year:  2004        PMID: 15135189     DOI: 10.1016/j.resuscitation.2003.12.019

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


  8 in total

1.  Safety and efficacy of defibrillator charging during ongoing chest compressions: a multi-center study.

Authors:  Dana P Edelson; Brian J Robertson-Dick; Trevor C Yuen; Joar Eilevstjønn; Deborah Walsh; Charles J Bareis; Terry L Vanden Hoek; Benjamin S Abella
Journal:  Resuscitation       Date:  2010-11       Impact factor: 5.262

2.  Capnography and chest-wall impedance algorithms for ventilation detection during cardiopulmonary resuscitation.

Authors:  Dana P Edelson; Joar Eilevstjønn; Elizabeth K Weidman; Elizabeth Retzer; Terry L Vanden Hoek; Benjamin S Abella
Journal:  Resuscitation       Date:  2009-12-29       Impact factor: 5.262

3.  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

4.  Deep Neural Network Approach for Continuous ECG-Based Automated External Defibrillator Shock Advisory System During Cardiopulmonary Resuscitation.

Authors:  Shirin Hajeb-M; Alicia Cascella; Matt Valentine; K H Chon
Journal:  J Am Heart Assoc       Date:  2021-03-05       Impact factor: 5.501

5.  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

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

8.  Enhancing ventilation detection during cardiopulmonary resuscitation by filtering chest compression artifact from the capnography waveform.

Authors:  Jose Julio Gutiérrez; Mikel Leturiondo; Sofía Ruiz de Gauna; Jesus María Ruiz; Luis Alberto Leturiondo; Digna María González-Otero; Dana Zive; James Knox Russell; Mohamud Daya
Journal:  PLoS One       Date:  2018-08-02       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.