TY - JOUR
T1 - Monitoring chest compression quality during cardiopulmonary resuscitation
T2 - Proof-ofconcept of a single accelerometer-based feedback algorithm
AU - Gonzáleza-Otero, Digna María
AU - Ruiz, Jesus María
AU - De Gauna, Sofía Ruiz
AU - Gutiérrez, Jose Julio
AU - Daya, Mohamud
AU - Russell, James Knox
AU - Azcarate, Izaskun
AU - Leturiondo, Mikel
N1 - Publisher Copyright:
© 2018 González-Otero et al. This is an open ccess article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and eproduction in any medium, provided the original author and source are credited.
PY - 2018/2
Y1 - 2018/2
N2 - Background The use of real-Time feedback systems to guide rescuers during cardiopulmonary resuscitation (CPR) significantly contributes to improve adherence to published resuscitation guidelines. Recently, we designed a novel method for computing depth and rate of chest compressions relying solely on the spectral analysis of chest acceleration. That method was extensively tested in a simulated manikin scenario. The purpose of this study is to report the results of this method as tested in human out-of-hospital cardiac arrest (OHCA) cases. Materials and methods The algorithm was evaluated retrospectively with seventy five OHCA episodes recorded by monitor-defibrillators equipped with a CPR feedback device. The acceleration signal and the compression signal computed by the CPR feedback device were stored in each episode. The algorithm was continuously applied to the acceleration signals. The depth and rate values estimated every 2-s from the acceleration data were compared to the reference values obtained from the compression signal. The performance of the algorithm was assesed in terms of the sensitivity and positive predictive value (PPV) for detecting compressions and in terms of its accuracy through the analysis of measurement error. Results The algorithm reported a global sensitivity and PPV of 99.98% and 99.79%, respectively. The median (P75) unsigned error in depth and rate was 0.9 (1.7) mm and 1.0 (1.7) cpm, respectively. In 95% of the analyzed 2-s windows the error was below 3.5 mm and 3.1 cpm, respectively. Conclusions The CPR feedback algorithm proved to be reliable and accurate when tested retrospectively with human OHCA episodes. A new CPR feedback device based on this algorithm could be helpful in the resuscitation field.
AB - Background The use of real-Time feedback systems to guide rescuers during cardiopulmonary resuscitation (CPR) significantly contributes to improve adherence to published resuscitation guidelines. Recently, we designed a novel method for computing depth and rate of chest compressions relying solely on the spectral analysis of chest acceleration. That method was extensively tested in a simulated manikin scenario. The purpose of this study is to report the results of this method as tested in human out-of-hospital cardiac arrest (OHCA) cases. Materials and methods The algorithm was evaluated retrospectively with seventy five OHCA episodes recorded by monitor-defibrillators equipped with a CPR feedback device. The acceleration signal and the compression signal computed by the CPR feedback device were stored in each episode. The algorithm was continuously applied to the acceleration signals. The depth and rate values estimated every 2-s from the acceleration data were compared to the reference values obtained from the compression signal. The performance of the algorithm was assesed in terms of the sensitivity and positive predictive value (PPV) for detecting compressions and in terms of its accuracy through the analysis of measurement error. Results The algorithm reported a global sensitivity and PPV of 99.98% and 99.79%, respectively. The median (P75) unsigned error in depth and rate was 0.9 (1.7) mm and 1.0 (1.7) cpm, respectively. In 95% of the analyzed 2-s windows the error was below 3.5 mm and 3.1 cpm, respectively. Conclusions The CPR feedback algorithm proved to be reliable and accurate when tested retrospectively with human OHCA episodes. A new CPR feedback device based on this algorithm could be helpful in the resuscitation field.
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U2 - 10.1371/journal.pone.0192810
DO - 10.1371/journal.pone.0192810
M3 - Article
C2 - 29444169
AN - SCOPUS:85042167437
SN - 1932-6203
VL - 13
JO - PloS one
JF - PloS one
IS - 2
M1 - e0192810
ER -