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Reducing CPR artefacts in ventricular fibrillation in vitro
A Langhelle1, T Eftestøl, H Myklebust
1Institute for Experimental Medical Research, Ulleval University Hospital, N-0407 Oslo, Norway. audun.langhelle@ioks.uio.no
Insights
A new adaptive filter effectively removes cardiopulmonary resuscitation (CPR) artifacts from electrocardiogram (ECG) signals during cardiac arrest. This allows for continuous rhythm analysis without pausing CPR, potentially improving patient outcomes.
Area of Science:
- Cardiology
- Biomedical Engineering
- Signal Processing
Background:
- Cardiopulmonary resuscitation (CPR) generates electrocardiogram (ECG) artifacts, necessitating pauses in chest compressions for rhythm analysis.
- These hands-off intervals during CPR compromise vital organ perfusion.
- Existing fixed coefficient filters are ineffective in humans due to overlapping frequency spectra of CPR artifacts and ventricular fibrillation (VF) signals.
Purpose of the Study:
- To develop and evaluate a novel digital adaptive filter for removing CPR-induced artifacts from human ECG signals.
- To compare the performance of the adaptive filter against a fixed coefficient filter in the presence of CPR artifacts.
- To assess the filter's efficacy across a range of signal-to-noise ratios (SNRs).
Main Methods:
- CPR artifacts from porcine models were mixed with human VF signals at SNRs ranging from -10 dB to +10 dB.
- A digital adaptive filter was developed to remove CPR artifacts.
- The adaptive filter's performance was compared to a fixed coefficient filter.
Main Results:
- The adaptive filter significantly outperformed the fixed coefficient filter in removing CPR artifacts across all tested SNR levels.
- At an initial SNR of 0 dB, the adaptive filter restored SNRs to 9.0 ± 0.7 dB, compared to 0.9 ± 0.7 dB for the fixed filter (P < 0.0001).
- The adaptive filter demonstrated superior performance in enhancing signal quality even at low SNRs.
Conclusions:
- A digital adaptive filter can effectively remove CPR artifacts from ECG signals during ongoing CPR.
- This technology has the potential to eliminate the need for hands-off intervals during rhythm analysis.
- Implementing this adaptive filter could lead to improved resuscitation outcomes by ensuring continuous chest compressions.
Abstract:
CPR creates artefacts on the ECG, and a pause in CPR is therefore mandatory during rhythm analysis. This hands-off interval is harmful to the already marginally circulated tissues during CPR, and if the artefacts could be removed by filtering, the rhythm could be analyzed during ongoing CPR. Fixed coefficient filters used in animals cannot solve this problem in humans, due to overlapping frequency spectra for artefacts and VF signals. In the present study, we established a method for mixing CPR-artefacts (noise) from a pig with human VF (signal) at various signal-to-noise ratios (SNR) from -10 dB to +10 dB. We then developed a new methodology for removing CPR artefacts by applying a digital adaptive filter, and compared the results with this filter to that of a fixed coefficient filter. The results with the adaptive filter clearly outperformed the fixed coefficient filter for all SNR levels. At an original SNR of 0 dB, the restored SNRs were 9.0+/-0.7 dB versus 0.9+/-0.7 dB respectively (P<0.0001).