title: Feedback on the Rate and Depth of Chest Compressions during Cardiopulmonary Resuscitation Using Only Accelerometers.
abstract: BACKGROUND
  Quality of cardiopulmonary resuscitation (CPR) is key to increase survival from cardiac arrest. Providing chest compressions with adequate rate and depth is difficult even for well-trained rescuers. The use of real-time feedback devices is intended to contribute to enhance chest compression quality. These devices are typically based on the double integration of the acceleration to obtain the chest displacement during compressions. The integration process is inherently unstable and leads to important errors unless boundary conditions are applied for each compression cycle. Commercial solutions use additional reference signals to establish these conditions, requiring additional sensors. Our aim was to study the accuracy of three methods based solely on the acceleration signal to provide feedback on the compression rate and depth.
  
  
  METHODS
  We simulated a CPR scenario with several volunteers grouped in couples providing chest compressions on a resuscitation manikin. Different target rates (80, 100, 120, and 140 compressions per minute) and a target depth of at least 50 mm were indicated. The manikin was equipped with a displacement sensor. The accelerometer was placed between the rescuer's hands and the manikin's chest. We designed three alternatives to direct integration based on different principles (linear filtering, analysis of velocity, and spectral analysis of acceleration). We evaluated their accuracy by comparing the estimated depth and rate with the values obtained from the reference displacement sensor.
  
  
  RESULTS
  The median (IQR) percent error was 5.9% (2.8-10.3), 6.3% (2.9-11.3), and 2.5% (1.2-4.4) for depth and 1.7% (0.0-2.3), 0.0% (0.0-2.0), and 0.9% (0.4-1.6) for rate, respectively. Depth accuracy depended on the target rate (p < 0.001) and on the rescuer couple (p < 0.001) within each method.
  
  
  CONCLUSIONS
  Accurate feedback on chest compression depth and rate during CPR is possible using exclusively the chest acceleration signal. The algorithm based on spectral analysis showed the best performance. Despite these encouraging results, further research should be conducted to asses the performance of these algorithms with clinical data.
authors.affiliation: Department of Communications Engineering, Faculty of Engineering, University of the Basque Country, Bilbao, Bizkaia, Spain.
authors.forename: Sofía
authors.initials: S
authors.lastname: Ruiz de Gauna
authors.affiliation: Department of Communications Engineering, Faculty of Engineering, University of the Basque Country, Bilbao, Bizkaia, Spain.
authors.forename: Digna M
authors.initials: DM
authors.lastname: González-Otero
authors.affiliation: Department of Communications Engineering, Faculty of Engineering, University of the Basque Country, Bilbao, Bizkaia, Spain.
authors.forename: Jesus
authors.initials: J
authors.lastname: Ruiz
authors.affiliation: Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, United States of America.
authors.forename: James K
authors.initials: JK
authors.lastname: Russell
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods*; D000465:Algorithms; D016887:Cardiopulmonary Resuscitation / Q000295:instrumentation / Q000379:methods*; D005246:Feedback; D006323:Heart Arrest / Q000628:therapy*; D006801:Humans; D008348:Manikins; D008962:Models, Theoretical; D011312:Pressure; D015203:Reproducibility of Results; D013909:Thorax / Q000503:physiopathology*; D013997:Time Factors