Rhythm Analysis during Cardiopulmonary Resuscitation : Past, Present, and Future

Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest compressions induce artifacts in the ECG. Unfortunately, interrupting CPR ad...

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Published in:BioMed research international Vol. 2014; no. 2014; pp. 1 - 13
Main Authors: Ruiz, Jesus, Ruiz de Gauna, Sofia, Eftestøl, Trygve, Aramendi, Elisabete, Ayala, Unai, Irusta, Unai
Format: Journal Article
Language:English
Published: Cairo, Egypt Hindawi Puplishing Corporation 01-01-2014
Hindawi Publishing Corporation
John Wiley & Sons, Inc
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Abstract Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest compressions induce artifacts in the ECG. Unfortunately, interrupting CPR adversely affects survival. In the last twenty years, research has been focused on designing methods for analysis of ECG during chest compressions. Most approaches are based either on adaptive filters to remove the CPR artifact or on robust algorithms which directly diagnose the corrupted ECG. In general, all the methods report low specificity values when tested on short ECG segments, but how to evaluate the real impact on CPR delivery of continuous rhythm analysis during CPR is still unknown. Recently, researchers have proposed a new methodology to measure this impact. Moreover, new strategies for fast rhythm analysis during ventilation pauses or high-specificity algorithms have been reported. Our objective is to present a thorough review of the field as the starting point for these late developments and to underline the open questions and future lines of research to be explored in the following years.
AbstractList Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest compressions induce artifacts in the ECG. Unfortunately, interrupting CPR adversely affects survival. In the last twenty years, research has been focused on designing methods for analysis of ECG during chest compressions. Most approaches are based either on adaptive filters to remove the CPR artifact or on robust algorithms which directly diagnose the corrupted ECG. In general, all the methods report low specificity values when tested on short ECG segments, but how to evaluate the real impact on CPR delivery of continuous rhythm analysis during CPR is still unknown. Recently, researchers have proposed a new methodology to measure this impact. Moreover, new strategies for fast rhythm analysis during ventilation pauses or high-specificity algorithms have been reported. Our objective is to present a thorough review of the field as the starting point for these late developments and to underline the open questions and future lines of research to be explored in the following years.
Audience Academic
Author Ruiz de Gauna, Sofia
Ayala, Unai
Irusta, Unai
Ruiz, Jesus
Aramendi, Elisabete
Eftestøl, Trygve
AuthorAffiliation 1 Communications Engineering Department, University of the Basque Country (UPV/EHU), Alameda Urquijo S/N, 48013 Bilbao, Spain
2 Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway
AuthorAffiliation_xml – name: 1 Communications Engineering Department, University of the Basque Country (UPV/EHU), Alameda Urquijo S/N, 48013 Bilbao, Spain
– name: 2 Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway
Author_xml – sequence: 1
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  fullname: Aramendi, Elisabete
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  fullname: Ayala, Unai
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  fullname: Irusta, Unai
BackLink https://www.ncbi.nlm.nih.gov/pubmed/24527445$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Contributor Ruiz de Gauna, Sofia
Ayala, Unai
Irusta, Unai
Ruiz, Jesus
Aramendi, Elisabete
Eftestøl, Trygve
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  fullname: Irusta, Unai
Copyright Copyright © 2014 Sofia Ruiz de Gauna et al.
COPYRIGHT 2014 John Wiley & Sons, Inc.
Copyright © 2014 Sofia Ruiz de Gauna et al. Sofia Ruiz de Gauna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright © 2014 Sofia Ruiz de Gauna et al. 2014
Copyright_xml – notice: Copyright © 2014 Sofia Ruiz de Gauna et al.
– notice: COPYRIGHT 2014 John Wiley & Sons, Inc.
– notice: Copyright © 2014 Sofia Ruiz de Gauna et al. Sofia Ruiz de Gauna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
– notice: Copyright © 2014 Sofia Ruiz de Gauna et al. 2014
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Snippet Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be...
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SubjectTerms Algorithms
Analysis
Biological rhythms
Cardiopulmonary resuscitation
Cardiopulmonary Resuscitation - methods
Chest Wall Oscillation - methods
Computer engineering
CPR
CPR (First aid)
Defibrillators
Electric Countershock
Electrocardiography - methods
Forecasts and trends
Health aspects
Heart attacks
Humans
Methods
Out-of-Hospital Cardiac Arrest - prevention & control
Out-of-Hospital Cardiac Arrest - therapy
Probability
Review
Rhythm
Studies
Ventilation
Title Rhythm Analysis during Cardiopulmonary Resuscitation : Past, Present, and Future
URI https://search.emarefa.net/detail/BIM-467983
https://dx.doi.org/10.1155/2014/386010
https://www.ncbi.nlm.nih.gov/pubmed/24527445
https://www.proquest.com/docview/1564214981
https://search.proquest.com/docview/1510108652
https://search.proquest.com/docview/1534841034
https://pubmed.ncbi.nlm.nih.gov/PMC3910663
Volume 2014
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