Literature DB >> 23778011

A review of the performance of artifact filtering algorithms for cardiopulmonary resuscitation.

Yushun Gong1, Bihua Chen, Yongqin Li.   

Abstract

Various filtering strategies have been adopted and investigated to suppress the cardiopulmonary resuscitation (CPR) artifact. In this article, two types of artifact removal methods are reviewed: one is the method that removes CPR artifact using only ECG signals, and the other is the method with additional reference signals, such as acceleration, compression depth and transthoracic impedance. After filtering, the signal-to-noise ratio is improved from 0 dB to greater than 2.8 dB, the sensitivity is increased to > 90% as recommended by the American Heart Association, whereas the specificity was far from the recommended 95%, which is considered to be the major drawback of the available artifact removal methods. The overall performance of the adaptive filtering methods with additional reference signal outperforms the methods using only ECG signals. Further research should focus on the refinement of artifact filtering methods and the improvement of shock advice algorithms with the presence of CPR.

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Year:  2013        PMID: 23778011     DOI: 10.1260/2040-2295.4.2.185

Source DB:  PubMed          Journal:  J Healthc Eng        ISSN: 2040-2295            Impact factor:   2.682


  8 in total

1.  Ventricular Fibrillation Waveform Analysis During Chest Compressions to Predict Survival From Cardiac Arrest.

Authors:  Jason Coult; Jennifer Blackwood; Lawrence Sherman; Thomas D Rea; Peter J Kudenchuk; Heemun Kwok
Journal:  Circ Arrhythm Electrophysiol       Date:  2019-01

2.  A Method to Detect Presence of Chest Compressions During Resuscitation Using Transthoracic Impedance.

Authors:  Jason Coult; Jennifer Blackwood; Thomas D Rea; Peter J Kudenchuk; Heemun Kwok
Journal:  IEEE J Biomed Health Inform       Date:  2019-05-24       Impact factor: 5.772

3.  Ventricular fibrillation waveform measures combined with prior shock outcome predict defibrillation success during cardiopulmonary resuscitation.

Authors:  Jason Coult; Heemun Kwok; Lawrence Sherman; Jennifer Blackwood; Peter J Kudenchuk; Thomas D Rea
Journal:  J Electrocardiol       Date:  2017-08-01       Impact factor: 1.438

4.  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

5.  Estimating the amplitude spectrum area of ventricular fibrillation during cardiopulmonary resuscitation using only ECG waveform.

Authors:  Feng Zuo; Youde Ding; Chenxi Dai; Liang Wei; Yushun Gong; Juan Wang; Yiming Shen; Yongqin Li
Journal:  Ann Transl Med       Date:  2021-04

6.  Automated Condition-Based Suppression of the CPR Artifact in ECG Data to Make a Reliable Shock Decision for AEDs during CPR.

Authors:  Shirin Hajeb-Mohammadalipour; Alicia Cascella; Matt Valentine; Ki H Chon
Journal:  Sensors (Basel)       Date:  2021-12-08       Impact factor: 3.576

Review 7.  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

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

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