Automated detection of asynchrony in patient-ventilator interaction.
Details
Serval ID
serval:BIB_11AC61138B6C
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automated detection of asynchrony in patient-ventilator interaction.
Journal
Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
ISSN
1557-170X (Print)
ISSN-L
1557-170X
Publication state
Published
Issued date
2009
Peer-reviewed
Oui
Volume
2009
Pages
5324-5327
Language
english
Notes
Publication types: Journal ArticlePublication Status: ppublish
Abstract
An automated classification algorithm for the detection of expiratory ineffective efforts in patient-ventilator interaction is developed and validated. Using this algorithm, 5624 breaths from 23 patients in a pulmonary ward were examined. The participants (N = 23) underwent both conventional and non-invasive ventilation. Tracings of patient flow, pressure at the airway, and transdiaphragmatic pressure were manually labeled by an expert. Overall accuracy of 94.5% was achieved with sensitivity 58.7% and specificity 98.7%. The results demonstrate the viability of using pattern classification techniques to automatically detect the presence of asynchrony between a patient and their ventilator.
Keywords
Automation/methods, Humans, Pressure, Respiratory Mechanics/physiology, Ventilators, Mechanical
Pubmed
Create date
27/06/2013 15:05
Last modification date
20/08/2019 13:39