Automated detection of asynchrony in patient-ventilator interaction

Author

Mulqueeny, Qestra ; Redmond, Stephen J. ; Tassaux, Didier ; Vignaux, Laurence ; Jolliet, Philippe ; Ceriana, Piero ; Nava, Stefano ; Schindhelm, Klaus ; Lovell, Nigel H.

Author_Institution

Grad. Sch. of Biomed. Eng., Univ. of New South Wales, Sydney, NSW, Australia

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

5324

Lastpage

5327

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

medical signal detection; medical signal processing; pneumodynamics; airflow; airway pressure; automated asynchrony detection; automated classification algorithm; expiratory ineffective efforts; patient-ventilator interaction; pattern classification; transdiaphragmatic pressure; ventilation; Automation; Humans; Pressure; Respiratory Mechanics; Ventilators, Mechanical;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5332684

Filename

5332684