Model-Based Estimation of Inspiratory Effort Using Surface EMG

Jan Grashoff*, Eike Petersen, Stephan Walterspacher, Philipp Rostalski

*Korrespondierende/r Autor/-in für diese Arbeit
1 Zitat (Scopus)

Abstract

Objective: The quantification of inspiratory patient effort in assisted mechanical ventilation is essential for the adjustment of ventilatory assistance and for assessing patient-ventilator interaction. The inspiratory effort is usually measured via the respiratory muscle pressure (Pmus) derived from esophageal pressure (Pes) measurements. As yet, no reliable non-invasive and unobtrusive alternatives exist to continuously quantify Pmus. Methods: We propose a model-based approach to estimate Pmus non-invasively during assisted ventilation using surface electromyographic (sEMG) measurements. The method combines the sEMG and ventilator signals to determine the lung elastance and resistance as well as the neuromechanical coupling of the respiratory muscles via a novel regression technique. Using the equation of motion, an estimate for Pmus can then be calculated directly from the lung mechanical parameters and the pneumatic ventilator signals. Results: The method was applied to data recorded from a total of 43 ventilated patients and validated against Pes-derived Pmus. Patient effort was quantified via the Pmus pressure-time-product (PTP). The sEMGderived PTP estimated using the proposed method was highly correlated to Pes-derived PTP (r = 0.95 ± 0.04), and the breath-wise deviation between the two quantities was -0.83 ± 1.73 cmH2Os. Conclusion: The estimated, sEMGderived Pmus is closely related to the Pes-based reference and allows to reliably quantify inspiratory effort. Significance: The proposed technique provides a valuable tool for physicians to assess patients undergoing assisted mechanical ventilation and, thus, may support clinical decision making.

OriginalspracheEnglisch
Aufsatznummer1
ZeitschriftIEEE Transactions on Biomedical Engineering
Jahrgang70
Ausgabenummer1
Seiten (von - bis)247-258
Seitenumfang12
ISSN0018-9294
DOIs
PublikationsstatusVeröffentlicht - 01.01.2023

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