Automated detection of asynchrony in patient-ventilator interaction.

Details

Serval ID
serval:BIB_11AC61138B6C
Type
Article: article from journal or magazin.
Collection
Publications
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
Author(s)
Mulqueeny Q., Redmond S.J., Tassaux D., Vignaux L., Jolliet P., Ceriana P., Nava S., Schindhelm K., Lovell N.H.
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 14:05
Last modification date
20/08/2019 12:39
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