Automating the correction of flow integration drift during whole-body plethysmography

Abstract

Prolonged measurement of total body volume variations (deltaVb) with whole-body, flow-based plethysmography (WBP) results in a drift of the signal due to changes in temperature and humidity inside the plethysmograph and to numerical integration of the flow to obtain deltaVb. This drift has been previously corrected with the application of a waveletbased filter using visual inspection of the signal to select the optimal filter level (Uva et al. Front. Physiol. 6:411, 2016), thus introducing potential operator bias. To exclude the latter we compared this approach with a newly developed automatic method based on (1) correction for actual changes in temperature and humidity inside the plethysmograph (algorithm TH) and (2) automatic selection of the wavelet filter level based on comparison between deltaVb and intra-thoracic and abdominal pressure variations measured simultaneously (algorithm WAV). The Pearson's correlation coefficient between deltaVb and the changes in volume of the chest wall (deltaVcw) simultaneously obtained by optoelectronic plethysmography (OEP) was calculated after correction of deltaVb with TH and WAV applied separately, TH and WAV applied consecutively (TH+WAV), manual selection of a wavelet filter based on visual inspection (MAN) or no correction (CTRL). The correlation between deltaVb and deltaVcw increased marginally with WAV, TH+WAV and MAN compared to CTRL (P < 0.01). Conversely, TH alone yielded a lower correlation (P < 0.01). It follows that while the automated wavelet filter level selection method (WAV) represents an effective, operator-independent method for the correction of deltaVb, whether or not it is combined with specific correction for changes in thermodynamic conditions inside the plethysmograph, the manual method (MAN) yields satisfactory results without the constraints of intra-thoracic and abdominal pressure measurement.

Priming the cardiodynamic phase of pulmonary oxygen uptake through voluntary modulations of the respiratory pump at the onset of exercise

“…Subtraction of the two signals yielded V bs . The drift in total body volume resulting from changes in thermodynamic conditions and from mathematical integration was corrected using an automated method based on synchronized measurements of temperature and humidity inside the cabin using a digital transducer (DHT22, Aosong, Guangzhou, China) and monitoring of oesophageal ( P oes ) and gastric ( P ga ) pressures variations, as previously described (Stucky et al., 2020). To measure P oes and P ga , two balloon‐tipped catheters attached to a pressure transducer (RCEM250DB, Sensortechnics, Puchheim, Germany) were inserted nasally and placed in the lower third of the oesophagus and the stomach, respectively.…”

Blood shifts between body compartments during submaximal exercise with induced expiratory flow limitation in healthy humans

“…Mathematical subtraction of the two signals yielded the volume of blood shifting between the trunk and the extremities [volume of blood shift (Vbs)] (Aliverti et al, 2009(Aliverti et al, , 2010LoMauro & Aliverti, 2018;Stucky et al, 2021;Uva et al, 2016). Before the computation of Vbs, a validated algorithm was used to correct the drift in the Vb signal attributable to changes in thermodynamic conditions based on measured values of temperature and humidity and automatically to select the level of a wavelet filter applied to remove the remaining drift in Vb attributable to numerical integration of the flow signal (Stucky et al, 2020).…”