Automated characterization of patient-ventilator interaction using surface electromyography.

Julia SauerJan GraßhoffNiklas M CarbonWilli M KochSteffen Weber-CarstensPhilipp Rostalski

Published in: Annals of intensive care (2024)

Our study demonstrates the feasibility of automating the quantification of patient-ventilator asynchrony in critically ill patients using noninvasive sEMG. This may facilitate more frequent diagnosis of asynchrony and support improving patient-ventilator interaction.

Keyphrases

case report
acute respiratory distress syndrome
mechanical ventilation
machine learning
deep learning
high throughput
single cell