A Method to Suppress Chest Compression Artifact Enhancing Capnography-Based Ventilation Guidance during Cardiopulmonary Resuscitation

Mikel Leturiondo, J. J. Gutierrez, Sofia Ruiz De Gauna, Jesus Ruiz, Luis A. Leturiondo, James K. Russell, Mohamud Daya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Capnography-based ventilation rate guidance is valuable and widely used by advanced life support during cardiopulmonary resuscitation (CPR). However, there is a high incidence of induced chest compression (CC) oscillations that decreases the reliability of automated ventilation detection. We used 30 out-of-hospital cardiac arrest episodes containing the capnogram and transthoracic impedance signals. The algorithm detects the presence of distorted ventilations in the capnogram. It calculates the artifact envelope during the alveolar plateau and removes the artifact during capnogram baseline, thus obtaining a non-distorted waveform. The goodness of the method was assessed by comparing the performance of a ventilation detection algorithm before and after artifact suppression. From a total of 6387 annotated ventilations, 34% of them were classified as distorted. Global sensitivity and positive predictive value (Se/PPV, %) improved from 77.9/74.0 to 97.0/95.8. Median value of the unsigned error (%) of the estimated ventilation rate decreased from 19.6 to 4.5 and the accuracy for detection of over-ventilation increased with cleaned capnograms. Capnogram-based ventilation guidance during CPR was enhanced after CC artifact suppression. Our method preserved the tracing of CO2 concentration caused by ventilations, allowing other clinical uses of the capnography during resuscitation.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology Conference, CinC 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781728109589
DOIs
StatePublished - Sep 2018
Event45th Computing in Cardiology Conference, CinC 2018 - Maastricht, Netherlands
Duration: Sep 23 2018Sep 26 2018

Publication series

NameComputing in Cardiology
Volume2018-September
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

Conference45th Computing in Cardiology Conference, CinC 2018
CountryNetherlands
CityMaastricht
Period9/23/189/26/18

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

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