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Communication Dans Un Congrès Année : 2013

Mechanical ventilation system monitoring : Automatic detection of dynamic hyperinlation and asynchrony

Résumé

Automatic monitoring of mechanical ventilation system becomes more and more important with respect to the number of patients per clinician. In this paper, the automatic detections of dynamic hyperinflation (PEEPi) and asynchrony in a monitoring framework are considered. The proposed detection methods are based on a robust non-parametric hypothesis testing, namely Random Distortion Testing (RDT), that requires no prior information on the signal distribution. The experiment results have shown that the proposed algorithms provide relevant detection of abnormalities during mechanical ventilation
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Dates et versions

hal-00946831 , version 1 (14-02-2014)

Identifiants

Citer

Quang Thang Nguyen, Dominique Pastor, François Lellouche, Erwan L'Her. Mechanical ventilation system monitoring : Automatic detection of dynamic hyperinlation and asynchrony. EMBC 2013 : 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jul 2013, Osaka, Japan. pp.5207 - 5210, ⟨10.1109/EMBC.2013.6610722⟩. ⟨hal-00946831⟩
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