Automatic detection of chest compressions for the assessment of CPR-quality parameters.

AIM Accurate chest compression detection is key to evaluate cardiopulmonary resuscitation (CPR) quality. Two automatic compression detectors were developed, for the compression depth (CD), and for the thoracic impedance (TI). The objective was to evaluate their accuracy for compression detection and for CPR quality assessment. METHODS Compressions were manually annotated using the force and ECG in 38 out-of-hospital resuscitation episodes, comprising 869 min and 67,402 compressions. Compressions were detected using a negative peak detector for the CD. For the TI, an adaptive peak detector based on the amplitude and duration of TI fluctuations was used. Chest compression rate (CC-rate) and chest compression fraction (CCF) were calculated for the episodes and for every minute within each episode. CC-rate for rescuer feedback was calculated every 8 consecutive compressions. RESULTS The sensitivity and positive predictive value were 98.4% and 99.8% using CD, and 94.2% and 97.4% using TI. The mean CCF and CC-rate obtained from both detectors showed no significant differences with those obtained from the annotations (P>0.6). The Bland-Altman analysis showed acceptable 95% limits of agreement between the annotations and the detectors for the per-minute CCF, per-minute CC-rate, and CC-rate for feedback. For the detector based on TI, only 3.7% of CC-rate feedbacks had an error larger than 5%. CONCLUSION Automatic compression detectors based on the CD and TI signals are very accurate. In most cases, episode review could safely rely on these detectors without resorting to manual review. Automatic feedback on rate can be accurately done using the impedance channel.

[1]  Judy Powell,et al.  Chest Compression Fraction Determines Survival in Patients With Out-of-Hospital Ventricular Fibrillation , 2009, Circulation.

[2]  Gavin D Perkins,et al.  European Resuscitation Council Guidelines for Resuscitation 2010 Section 4. Adult advanced life support. , 2010, Resuscitation.

[3]  T. Eftestøl,et al.  Suppression of the cardiopulmonary resuscitation artefacts using the instantaneous chest compression rate extracted from the thoracic impedance. , 2012, Resuscitation.

[4]  L. Wik,et al.  Transthoracic impedance used to evaluate performance of cardiopulmonary resuscitation during out of hospital cardiac arrest. , 2008, Resuscitation.

[5]  Johannes Bickenbach,et al.  CPREzy improves performance of external chest compressions in simulated cardiac arrest. , 2007, Resuscitation.

[6]  J. Bache.  European Resuscitation Council Guidelines for Resuscitation , 1998 .

[7]  Dana Niles,et al.  The prevalence of chest compression leaning during in-hospital cardiopulmonary resuscitation. , 2011, Resuscitation.

[8]  K. Monsieurs,et al.  Excessive chest compression rate is associated with insufficient compression depth in prehospital cardiac arrest. , 2012, Resuscitation.

[9]  Irena Jekova,et al.  Shock advisory system with minimal delay triggering after end of chest compressions: accuracy and gained hands-off time. , 2011, Resuscitation.

[10]  Charles F Babbs,et al.  A new paradigm for human resuscitation research using intelligent devices. , 2008, Resuscitation.

[11]  Henry E. Wang,et al.  Comparison of methods for the determination of cardiopulmonary resuscitation chest compression fraction. , 2012, Resuscitation.

[12]  Judy Powell,et al.  The impact of increased chest compression fraction on return of spontaneous circulation for out-of-hospital cardiac arrest patients not in ventricular fibrillation. , 2011, Resuscitation.

[13]  J. Soar,et al.  The use of CPR feedback/prompt devices during training and CPR performance: A systematic review. , 2009, Resuscitation.

[14]  Helge Myklebust,et al.  CPR quality improvement during in-hospital cardiac arrest using a real-time audiovisual feedback system. , 2007, Resuscitation.

[15]  D. Davis,et al.  Relationship Between Chest Compression Rates and Outcomes From Cardiac Arrest , 2012, Circulation.

[16]  Jo Kramer-Johansen,et al.  Quality of out-of-hospital cardiopulmonary resuscitation with real time automated feedback: a prospective interventional study. , 2006, Resuscitation.

[17]  D. Davis,et al.  Minimizing pre- and post-defibrillation pauses increases the likelihood of return of spontaneous circulation (ROSC). , 2010, Resuscitation.

[18]  B. Abella,et al.  Chest Compression Rates During Cardiopulmonary Resuscitation Are Suboptimal: A Prospective Study During In-Hospital Cardiac Arrest , 2005, Circulation.

[19]  B. Abella,et al.  Safety and efficacy of defibrillator charging during ongoing chest compressions: a multi-center study. , 2010, Resuscitation.

[20]  Jo Kramer-Johansen,et al.  Effects of compression depth and pre-shock pauses predict defibrillation failure during cardiac arrest. , 2006, Resuscitation.

[21]  Rolf Rossaint,et al.  New visual feedback device improves performance of chest compressions by professionals in simulated cardiac arrest. , 2010, Resuscitation.

[22]  Douglas G. Altman,et al.  Measurement in Medicine: The Analysis of Method Comparison Studies , 1983 .

[23]  B. Abella,et al.  Uniform reporting of measured quality of cardiopulmonary resuscitation (CPR). , 2007, Resuscitation.

[24]  J. Krouwer.  Why Bland–Altman plots should use X, not (Y+X)/2 when X is a reference method , 2008, Statistics in medicine.

[25]  Adam Almozlino,et al.  Cardiopulmonary resuscitation feedback improves the quality of chest compression provided by hospital health care professionals. , 2011, The American journal of emergency medicine.

[26]  Cpr , 2005, Key Topics In Anaesthesia.

[27]  B. Abella,et al.  Capnography and chest-wall impedance algorithms for ventilation detection during cardiopulmonary resuscitation. , 2010, Resuscitation.

[28]  T. Rea,et al.  Performance of chest compressions by laypersons during the Public Access Defibrillation Trial. , 2010, Resuscitation.

[29]  Trygve Eftestøl,et al.  Impedance-Based Ventilation Detection During Cardiopulmonary Resuscitation , 2007, IEEE Transactions on Biomedical Engineering.

[30]  Jo Kramer-Johansen,et al.  Quality of cardiopulmonary resuscitation during out-of-hospital cardiac arrest , 2005 .

[31]  Sven Ole Aase,et al.  Compression depth estimation for CPR quality assessment using DSP on accelerometer signals , 2002, IEEE Transactions on Biomedical Engineering.

[32]  P. Steen,et al.  Advanced cardiac life support before and after tracheal intubation--direct measurements of quality. , 2006, Resuscitation.

[33]  Kari Anne Haaland Thorsen,et al.  Representing resuscitation data-Considerations on efficient analysis of quality of cardiopulmonary resuscitation. , 2009, Resuscitation.

[34]  Maaret Castrén,et al.  European Resuscitation Council Guidelines for Resuscitation 2010 Section 2. Adult basic life support and use of automated external defibrillators , 2010, Resuscitation.

[35]  Judy Powell,et al.  Perishock Pause: An Independent Predictor of Survival From Out-of-Hospital Shockable Cardiac Arrest , 2011, Circulation.

[36]  B. Abella,et al.  Quality of cardiopulmonary resuscitation during in-hospital cardiac arrest. , 2005, JAMA.

[37]  Trygve Eftestøl,et al.  Thoracic-impedance changes measured via defibrillator pads can monitor signs of circulation. , 2007, Resuscitation.

[38]  B. Abella,et al.  The effect of real-time CPR feedback and post event debriefing on patient and processes focused outcomes: A cohort study: trial protocol , 2011, Scandinavian journal of trauma, resuscitation and emergency medicine.

[39]  J. Tibballs,et al.  Adult advanced life support , 1994 .