Event-triggered averaging of electrical impedance tomography (EIT) respiratory waveforms as compared to low-pass filtering for removal of cardiac related impedance changes

Abstract

Electrical impedance tomography (EIT) is used for bedside ventilation monitoring; cardiac related impedance changes represent a source of noise superimposed on the ventilation signal, commonly removed by low-pass filtering (LPF). We investigated if an alternative approach, based on an event-triggered averaging (ETA) process, is more effective at preserving the actual ventilation waveform. Ten paralyzed patients undergoing volume-controlled ventilation were studied; 30 breaths for each patient were identified to compare LPF and ETA. For ETA the identified breaths were temporally aligned on the beginning of inspiration; the values of the thirty curves at each time point were averaged. The analysis was conducted on the global EIT signal and on four ventral-to-dorsal regions of interest. Global tidal variations by ETA resulted higher than LPF (average difference 139 ± 88 arbitrary units, p = 0.004). Both for global and regional waveforms, minimum and maximum EIT slopes were steeper by ETA as compared to LPF (average difference respectively − 57 ± 60 mL/s and 144 ± 96 mL/s for global signal, p < 0.05); ventilator inspiratory peak airflow correlated with maximum slope measured by ETA (r = 0.902, p < 0.001), but not LPF (p = 0.319). Beginning of inspiration identified on the ventilator waveform and on the global EIT signal by ETA occurred simultaneously, (+ 0.04 ± 0.07 s, p = 0.081), while occurred earlier by LPF (− 0.26 ± 0.1 s, p < 0.001). Removal of cardiac related impedance changes by ETA results in a ventilation signal more similar to the waveforms recorded by the ventilator, particularly regarding the slope of impedance changes and time at the minimum values as compared to LPF.