Academic Journal
In-silico credibility assessment of a computational physiological model for non-invasive monitoring of respiratory effort in critically ill patients.
| Τίτλος: | In-silico credibility assessment of a computational physiological model for non-invasive monitoring of respiratory effort in critically ill patients. |
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| Συγγραφείς: | Warnaar RSP; Cardiovascular and Respiratory Physiology, Technical Medical Center, University of Twente, Enschede, The Netherlands., Geraats S; Biomedical Engineering & Technical Medicine, University of Twente, Enschede, The Netherlands., Cornet AD; Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands., Aarts RGKM; Control and Mechatronics, University of Twente, Enschede, The Netherlands., Graßhoff J; Fraunhofer Research Institution for Individualized Medical Technology and Engineering IMTE, Lübeck, Germany., Donker DW; Cardiovascular and Respiratory Physiology, Technical Medical Center, University of Twente, Enschede, The Netherlands.; Department of Intensive Care, University Medical Centre Utrecht, Utrecht, The Netherlands., Oppersma E; Cardiovascular and Respiratory Physiology, Technical Medical Center, University of Twente, Enschede, The Netherlands. |
| Πηγή: | Physiological measurement [Physiol Meas] 2026 Sep 25; Vol. 47 (9). Date of Electronic Publication: 2026 Sep 25. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: IOP Pub. Ltd Country of Publication: England NLM ID: 9306921 Publication Model: Electronic Cited Medium: Internet ISSN: 1361-6579 (Electronic) Linking ISSN: 09673334 NLM ISO Abbreviation: Physiol Meas Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Bristol, UK : IOP Pub. Ltd., c1993- |
| Ιατρικοί όροι (MeSH): | Critical Illness* , Models, Biological* , Computer Simulation*, Monitoring, Physiologic/methods ; Respiratory Muscles/physiopathology ; Humans ; Electromyography ; Respiration, Artificial ; Reproducibility of Results |
| Περίληψη: | Objective.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 () 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 () 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 lowvariability (< 5.0 cmH (Creative Commons Attribution license.) |
| Contributed Indexing: | Keywords: computational physiological model; mechanical ventilation; neuro-mechanical coupling; respiratory effort; respiratory failure; respiratory surface electromyography |
| Entry Date(s): | Date Created: 20260911 Date Completed: 20260925 Latest Revision: 20260925 |
| Update Code: | 20260925 |
| DOI: | 10.1088/1361-6579/aea685 |
| PMID: | 42727606 |
| Βάση Δεδομένων: | MEDLINE |
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