Open-loop adaptive filtering for suppressing chest compression oscillations in the capnogram during cardiopulmonary resuscitation

Mikel Leturiondo, Jesús Ruiz, J. J. Gutiérrez, Luis A. Leturiondo, James K. Russell, Mohamud Ramzan Daya

Research output: Contribution to journalConference article

Abstract

Capnography is often used for the guidance on ventilation rate during cardiopulmonary resuscitation (CPR). However, capnogram waveform frequently presents oscillations induced by chest compressions (CC), affecting the reliability of ventilation detection. The aim of the work was to evaluate the performance of an open-loop adaptive filter in the cancellation of CC oscillations in the capnogram during CPR. For that purpose, we analyzed 60 episodes from an out-of-hospital (OOH) cardiac arrest registry maintained by TVF&R agency (USA). In 50% of the episodes the capnogram was corrupted by CC oscillations. The goodness of the filtering scheme was assessed by comparing the sensitivity (Se) and the positive predictive value (PPV) of an automated ventilation detector before and after filtering. A fixed-coefficient low-pass filter was also designed for comparison. The results showed that both filters reported a good performance although the adaptive scheme presented a slightly higher PPV (+1.2 points globally). The simpler fixed-coefficient scheme avoids the reference signal, but requires validation with larger datasets to ensure stability.

Original languageEnglish (US)
Pages (from-to)1-4
Number of pages4
JournalComputing in Cardiology
Volume44
DOIs
StatePublished - Jan 1 2017
Event44th Computing in Cardiology Conference, CinC 2017 - Rennes, France
Duration: Sep 24 2017Sep 27 2017

Fingerprint

Resuscitation
Adaptive filtering
Cardiopulmonary Resuscitation
Ventilation
Thorax
Capnography
Out-of-Hospital Cardiac Arrest
Low pass filters
Adaptive filters
Registries
Detectors

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

Cite this

Open-loop adaptive filtering for suppressing chest compression oscillations in the capnogram during cardiopulmonary resuscitation. / Leturiondo, Mikel; Ruiz, Jesús; Gutiérrez, J. J.; Leturiondo, Luis A.; Russell, James K.; Daya, Mohamud Ramzan.

In: Computing in Cardiology, Vol. 44, 01.01.2017, p. 1-4.

Research output: Contribution to journalConference article

Leturiondo, Mikel ; Ruiz, Jesús ; Gutiérrez, J. J. ; Leturiondo, Luis A. ; Russell, James K. ; Daya, Mohamud Ramzan. / Open-loop adaptive filtering for suppressing chest compression oscillations in the capnogram during cardiopulmonary resuscitation. In: Computing in Cardiology. 2017 ; Vol. 44. pp. 1-4.
@article{dde4c360b30648f69efdc37f3b6b20e3,
title = "Open-loop adaptive filtering for suppressing chest compression oscillations in the capnogram during cardiopulmonary resuscitation",
abstract = "Capnography is often used for the guidance on ventilation rate during cardiopulmonary resuscitation (CPR). However, capnogram waveform frequently presents oscillations induced by chest compressions (CC), affecting the reliability of ventilation detection. The aim of the work was to evaluate the performance of an open-loop adaptive filter in the cancellation of CC oscillations in the capnogram during CPR. For that purpose, we analyzed 60 episodes from an out-of-hospital (OOH) cardiac arrest registry maintained by TVF&R agency (USA). In 50{\%} of the episodes the capnogram was corrupted by CC oscillations. The goodness of the filtering scheme was assessed by comparing the sensitivity (Se) and the positive predictive value (PPV) of an automated ventilation detector before and after filtering. A fixed-coefficient low-pass filter was also designed for comparison. The results showed that both filters reported a good performance although the adaptive scheme presented a slightly higher PPV (+1.2 points globally). The simpler fixed-coefficient scheme avoids the reference signal, but requires validation with larger datasets to ensure stability.",
author = "Mikel Leturiondo and Jes{\'u}s Ruiz and Guti{\'e}rrez, {J. J.} and Leturiondo, {Luis A.} and Russell, {James K.} and Daya, {Mohamud Ramzan}",
year = "2017",
month = "1",
day = "1",
doi = "10.22489/CinC.2017.113-073",
language = "English (US)",
volume = "44",
pages = "1--4",
journal = "Computing in Cardiology",
issn = "2325-8861",
publisher = "IEEE Computer Society",

}

TY - JOUR

T1 - Open-loop adaptive filtering for suppressing chest compression oscillations in the capnogram during cardiopulmonary resuscitation

AU - Leturiondo, Mikel

AU - Ruiz, Jesús

AU - Gutiérrez, J. J.

AU - Leturiondo, Luis A.

AU - Russell, James K.

AU - Daya, Mohamud Ramzan

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Capnography is often used for the guidance on ventilation rate during cardiopulmonary resuscitation (CPR). However, capnogram waveform frequently presents oscillations induced by chest compressions (CC), affecting the reliability of ventilation detection. The aim of the work was to evaluate the performance of an open-loop adaptive filter in the cancellation of CC oscillations in the capnogram during CPR. For that purpose, we analyzed 60 episodes from an out-of-hospital (OOH) cardiac arrest registry maintained by TVF&R agency (USA). In 50% of the episodes the capnogram was corrupted by CC oscillations. The goodness of the filtering scheme was assessed by comparing the sensitivity (Se) and the positive predictive value (PPV) of an automated ventilation detector before and after filtering. A fixed-coefficient low-pass filter was also designed for comparison. The results showed that both filters reported a good performance although the adaptive scheme presented a slightly higher PPV (+1.2 points globally). The simpler fixed-coefficient scheme avoids the reference signal, but requires validation with larger datasets to ensure stability.

AB - Capnography is often used for the guidance on ventilation rate during cardiopulmonary resuscitation (CPR). However, capnogram waveform frequently presents oscillations induced by chest compressions (CC), affecting the reliability of ventilation detection. The aim of the work was to evaluate the performance of an open-loop adaptive filter in the cancellation of CC oscillations in the capnogram during CPR. For that purpose, we analyzed 60 episodes from an out-of-hospital (OOH) cardiac arrest registry maintained by TVF&R agency (USA). In 50% of the episodes the capnogram was corrupted by CC oscillations. The goodness of the filtering scheme was assessed by comparing the sensitivity (Se) and the positive predictive value (PPV) of an automated ventilation detector before and after filtering. A fixed-coefficient low-pass filter was also designed for comparison. The results showed that both filters reported a good performance although the adaptive scheme presented a slightly higher PPV (+1.2 points globally). The simpler fixed-coefficient scheme avoids the reference signal, but requires validation with larger datasets to ensure stability.

UR - http://www.scopus.com/inward/record.url?scp=85045127703&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045127703&partnerID=8YFLogxK

U2 - 10.22489/CinC.2017.113-073

DO - 10.22489/CinC.2017.113-073

M3 - Conference article

AN - SCOPUS:85045127703

VL - 44

SP - 1

EP - 4

JO - Computing in Cardiology

JF - Computing in Cardiology

SN - 2325-8861

ER -