A method for suppressing cardiogenic oscillations in impedance pneumography

Area of Science:

• Biomedical Engineering
• Physiological Monitoring
• Signal Processing

Background:

• Transthoracic electrical impedance signals reflect both cardiac and respiratory functions.
• In impedance pneumography (IP), cardiogenic oscillations (CGOs) are considered noise that can impede accurate lung function assessment.
• Effective CGO attenuation is crucial for reliable pulmonary flow parameter determination without distorting respiratory signals.

Purpose of the Study:

• To evaluate a modified filtering technique for attenuating CGOs in IP signals.
• To adapt a previously described filtering method for CGO removal in esophageal pressure signals to the IP context.
• To develop a lung volume-dependent parametric model for CGO waveform to improve filtering accuracy.

Main Methods:

• Assessed the suitability of an ensemble averaging filter, triggered by the electrocardiogram (ECG) R-wave, for CGO attenuation in IP.
• Modified the filtering technique to incorporate a lung volume-dependent parametric model of the CGO waveform.
• Compared the proposed method against low-pass and Savitzky-Golay filters using simultaneous ECG, IP, and pneumotachograph (PNT) recordings from 41 healthy adults.

Main Results:

• The proposed filtering method achieved excellent CGO attenuation, averaging 35.0±12.5 dB (mean±SD).
• The technique demonstrated minimal distortion of the respiratory component of the impedance signal.
• Performance was superior to traditional low-pass and Savitzky-Golay filtering methods in terms of CGO removal and signal integrity.

Conclusions:

• The modified ensemble averaging filter is highly effective for attenuating CGOs in impedance pneumography signals.
• This method offers a significant improvement for accurate lung function analysis by preserving the respiratory signal quality.
• The lung volume-dependent parametric model enhances the filter's ability to handle variations in CGO waveforms.