Literature DB >> 20732603

Cardiopulmonary resuscitation artefact suppression using a Kalman filter and the frequency of chest compressions as the reference signal.

Jesus Ruiz1, Unai Irusta, Sofia Ruiz de Gauna, Trygve Eftestøl.   

Abstract

AIM: To develop a new method to suppress the artefact generated by chest compressions during cardiopulmonary resuscitation (CPR) using only the frequency of the compressions as additional information.
MATERIALS AND METHODS: The CPR artefact suppression method was developed and tested using a database of 381 ECG records (89 shockable and 292 non-shockable) from 299 patients. All records were extracted from real out-of-hospital cardiac arrest episodes. The suppression method consists of a Kalman filter that uses the frequency of the measured compressions to estimate the artefact and to remove it from the ECG. The performance of the filter was evaluated by comparing the sensitivity and specificity of an automated external defibrillator before and after the artefact suppression.
RESULTS: For the test database, the sensitivity improved from 57.8% (95% confidence interval, 43.3-71.0%) to 93.3% (81.5-98.4%) and the specificity decreased from 92.5% (87.0-95.9%) to 89.1% (83.0-93.3%).
CONCLUSION: For a similar sensitivity, we obtained better specificity than that reported for other methods, although still short of the values recommended by the American Heart Association. The results suggest that the CPR artefact can be accurately modelled using only the frequency of the compressions. This information could be easily acquired through the defibrillator's CPR help pads, with minimal hardware modifications. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 20732603     DOI: 10.1016/j.resuscitation.2010.02.031

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


  4 in total

1.  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

2.  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 3.  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

4.  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

  4 in total

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