Related Experiment Video
Updated: May 17, 2026
Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
Published on: September 16, 2019
Effect of leak and breathing pattern on the accuracy of tidal volume estimation by commercial home ventilators: a
Manel Luján1, Ana Sogo, Xavier Pomares
1Department of Pneumology, Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Universitat Autònoma de Barcelona, Spain. mlujan@tauli.cat
Background:
New home ventilators are able to provide clinicians data of interest through built-in software. Monitoring of tidal volume (VT) is a key point in the assessment of the efficacy of home mechanical ventilation.
Objective:
To assess the reliability of the VT provided by 5 ventilators in a bench test.
Methods:
Five commercial ventilators from 4 different manufacturers were tested in pressure support mode with the help of a breathing simulator under different conditions of mechanical respiratory pattern, inflation pressure, and intentional leakage. Values provided by the built-in software of each ventilator were compared breath to breath with the VT monitored through an external pneumotachograph. Ten breaths for each condition were compared for every tested situation.
Results:
All tested ventilators underestimated VT (ranges of -21.7 mL to -83.5 mL, which corresponded to -3.6% to -14.7% of the externally measured VT). A direct relationship between leak and underestimation was found in 4 ventilators, with higher underestimations of the VT when the leakage increased, ranging between -2.27% and -5.42% for each 10 L/min increase in the leakage. A ventilator that included an algorithm that computes the pressure loss through the tube as a function of the flow exiting the ventilator had the minimal effect of leaks on the estimation of VT (0.3%). In 3 ventilators the underestimation was also influenced by mechanical pattern (lower underestimation with restrictive, and higher with obstructive).
Conclusions:
The inclusion of algorithms that calculate the pressure loss as a function of the flow exiting the ventilator in commercial models may increase the reliability of VT estimation.
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