title: Filtering mechanical chest compression artefacts from out-of-hospital cardiac arrest data.
abstract: OBJECTIVE
  Filtering techniques to remove manual compression artefacts from the ECG have not been incorporated to defibrillators to diagnose the rhythm during cardiopulmonary resuscitation. Mechanical and manual compression artefacts may be very different. The aim of this study is to characterize the compression artefact caused by the LUCAS 2 device and to evaluate whether filtering the LUCAS 2 artefact results in an accurate rhythm analysis.
  
  
  METHODS
  A dataset of 1045 segments were obtained from 230 out-of-hospital cardiac arrest (OHCA) patients after LUCAS 2 activation. Rhythms were 201 shockable, 270 asystole and 574 organized. Segments during asystole were used to characterize the artefact in time and frequency domains. Three filtering methods, a comb filter and two adaptive filters, were used to remove the mechanical compression artefact. The filtered ECG was then diagnosed with a shock decision algorithm from a defibrillator.
  
  
  RESULTS
  When compared to the manual compression artefact, the LUCAS 2 artefact presented a similar amplitude (1.2 mV, p-value 0.26), fixed frequency (101.7 min(-1)), more harmonic components, smaller spectral dispersion, and a more regular waveform (p-val <3 × 10(-7)). The sensitivity (SE) and specificity (SP) before filtering the LUCAS 2 artefact were 52.8% (90% low CI, 46.0%) and 81.5% (79.0%), respectively. For the best filter, SE and SP after filtering were 97.9% (95.7%) and 84.1% (82.0%), respectively. Optimal filters require more harmonics and smaller bandwidths than for manual compressions.
  
  
  CONCLUSIONS
  Filtering resulted in a large increase in SE and small increase in SP. Despite differences in artefact characteristics between manual and mechanical compressions, filtering the LUCAS 2 compression artefact results in SE/SP values comparable to those obtained for manual compression artefacts. The SP is still below the 95% recommended by the American Heart Association.
authors.affiliation: Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain. Electronic address: elisabete.aramendi@ehu.eus.
authors.forename: E
authors.initials: E
authors.lastname: Aramendi
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: U
authors.initials: U
authors.lastname: Ayala
authors.affiliation: National Advisory Unit for Prehospital Emergency Medicine (NAKOS) and Department of Anaesthesiology, Oslo University Hospital and University of Oslo, P.O. Box 4956 Nydalen, N-0424 Oslo, Norway.
authors.forename: H
authors.initials: H
authors.lastname: Naas
authors.affiliation: National Advisory Unit for Prehospital Emergency Medicine (NAKOS) and Department of Anaesthesiology, Oslo University Hospital and University of Oslo, P.O. Box 4956 Nydalen, N-0424 Oslo, Norway.
authors.forename: J
authors.initials: J
authors.lastname: Kramer-Johansen
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
mesh_terms: D000368:Aged; D016477:Artifacts; D047548:Defibrillators; D004562:Electrocardiography; D005260:Female; D006336:Heart Massage / Q000295:instrumentation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D058687:Out-of-Hospital Cardiac Arrest / Q000503:physiopathology* / Q000628:therapy*; D012815:Signal Processing, Computer-Assisted; D016896:Treatment Outcome
keywords: Cardiac arrest; Cardiopulmonary resuscitation; Mechanical chest compression; Rhythm analysis