Filtering mechanical chest compression artefacts from out-of-hospital cardiac arrest data
E Aramendi1, U Irusta1, U Ayala1
1Communications Engineering Department, University of the Basque Country UPV/EHU, Alameda Urquijo S/N, 48013 Bilbao, Spain.
Resuscitation
|November 8, 2015
Summary
Filtering mechanical compression artefacts from defibrillators significantly improves electrocardiogram (ECG) rhythm analysis during cardiopulmonary resuscitation. This enhances the accuracy of diagnosing cardiac arrest rhythms, crucial for effective treatment.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Device Technology
Background:
- Automated external defibrillators (AEDs) require accurate electrocardiogram (ECG) interpretation for rhythm diagnosis during cardiopulmonary resuscitation (CPR).
- Manual chest compressions create artefacts in ECG signals that can hinder accurate rhythm analysis.
- The integration of mechanical CPR devices, like the LUCAS 2, introduces distinct artefacts that require specific filtering techniques.
Purpose of the Study:
- To characterize the artefact produced by the LUCAS 2 mechanical chest compression device.
- To evaluate the effectiveness of filtering techniques in removing LUCAS 2 artefacts from ECG signals.
- To determine if filtering improves the accuracy of rhythm analysis for defibrillation during CPR.
Main Methods:
- Analysis of 1045 ECG segments from out-of-hospital cardiac arrest (OHCA) patients with LUCAS 2 device activation.
- Characterization of LUCAS 2 artefacts in time and frequency domains using segments during asystole.
- Application of three filtering methods (comb filter, two adaptive filters) to remove mechanical compression artefacts.
- Diagnosis of heart rhythms using a standard defibrillator shock decision algorithm on filtered and unfiltered ECGs.
Main Results:
- LUCAS 2 artefacts exhibit similar amplitude but different frequency and waveform characteristics compared to manual compression artefacts.
- Unfiltered LUCAS 2 ECGs showed low sensitivity (52.8%) and specificity (81.5%) for rhythm analysis.
- Post-filtering, the best method achieved high sensitivity (97.9%) and improved specificity (84.1%).
- Optimal filters for mechanical artefacts require more harmonics and narrower bandwidths than for manual artefacts.
Conclusions:
- Filtering significantly enhances sensitivity for rhythm analysis in the presence of LUCAS 2 artefacts.
- While specificity improved, it remained below the American Heart Association's recommended 95% threshold.
- Filtering mechanical compression artefacts can yield rhythm analysis comparable to that of manual compression artefacts, improving defibrillator efficacy.
