In-silico credibility assessment of a computational physiological model for non-invasive monitoring of respiratory effort in critically ill patients.

Authors

Rob Simon Petrus Warnaar, Stijn Geraats, Alexander D Cornet, Ronald G K M Aarts, Jan Grasshoff, Dirk W W Donker, Eline Oppersma

Published in

Physiological measurement. Sep 11, 2026. Epub Sep 11, 2026.

Abstract

Monitoring respiratory effort in critically ill patients during assisted mechanical ventilation is essential to individualize ventilatory support and prevent over- or underassistance. A non-invasive method to estimate respiratory muscle pressure (P_mus) combines respiratory surface electromyography (sEMG) with ventilator pressure-flow waveforms through the integrated equation of motion (iEqM). Implemented within a computational physiological model (CPM), the iEqM links muscle activation to generated pressure. This study investigates the reliability of an iEqM-based CPM under critical care conditions. Approach: CPM performance to estimate respiratory muscle pressure-time product ((PTP) ̂_mus) was evaluated in-silico using simulated patient profiles. Credibility activities included numerical verification, Monte-Carlo-based uncertainty quantification, and sensitivity analysis, exploring variations in respiratory mechanics, effort variability, sEMG signal quality, and patient-ventilator timing. Model outputs were compared with simulated reference values, with an acceptable clinical error margin set at 20%. Main results: Verification confirmed correct model implementation (errors < 0.3%). Input data uncertainty quantification showed limited variability (SD 1.8%). Sensitivity analysis revealed reduced accuracy under low P_mus variability (< 5.0 cmH₂O), low sEMG signal-to-noise ratios ((SNR) ̂ < 1.4), high P_mus magnitudes (17.5 cmH₂O), and persistent inspiratory efforts during expiration. Calibration using end-expiratory occlusion maneuvers improved accuracy, except at the lowest P_mus magnitude and (SNR) ̂s. Significance: The iEqM performs reliably when calibrated via end-expiratory occlusion maneuvers. Without calibration, accuracy declined with lower effort variability, poorer sEMG quality, or patient-ventilator asynchrony. These findings emphasize the need for context-aware application, accounting for patient-specific mechanics, signal integrity and ventilator interaction, to ensure credible and reliable monitoring of respiratory effort in critically ill patients.

PMID:
42727606
Bibliographic data and abstract were imported from PubMed on 12 Sep 2026.

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