title: Automatic detection of chest compressions for the assessment of CPR-quality parameters.
abstract: OBJECTIVE
  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%.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway; Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain. Electronic address: unai.ayala@ehu.es.
authors.forename: U
authors.initials: U
authors.lastname: Ayala
authors.affiliation: Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway.
authors.forename: T
authors.initials: T
authors.lastname: Eftestøl
authors.affiliation: Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain.
authors.forename: E
authors.initials: E
authors.lastname: Alonso
authors.affiliation: Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain.
authors.forename: U
authors.initials: U
authors.lastname: Irusta
authors.affiliation: Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain.
authors.forename: E
authors.initials: E
authors.lastname: Aramendi
authors.affiliation: Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger, 4036 Stavanger, Norway.
authors.forename: S
authors.initials: S
authors.lastname: Wali
authors.affiliation: Norwegian Centre for Prehospital Emergency Care (NAKOS), OsloUniversity Hospital and University of Oslo, Pb 4956 Nydalen, 0424 Oslo, Norway.
authors.forename: J
authors.initials: J
authors.lastname: Kramer-Johansen
mesh_terms: D016887:Cardiopulmonary Resuscitation / Q000592:standards*; D004562:Electrocardiography; D004632:Emergency Medical Services; D006801:Humans; D058687:Out-of-Hospital Cardiac Arrest / Q000628:therapy*; D011237:Predictive Value of Tests; D011312:Pressure; D011446:Prospective Studies; D011787:Quality of Health Care; D012680:Sensitivity and Specificity
keywords: Automated external defibrillator (AED); Cardiac arrest; Cardiopulmonary resuscitation (CPR); Chest compression; Transthoracic impedance