Use of basis functions within a non-linear autoregressive model of pulmonary mechanics-Reference-Cited by-同舟云学术

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Use of basis functions within a non-linear autoregressive model of pulmonary mechanics

Published:2016-05 Issue: Volume:27 Page:44-50
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Langdon Ruby,Docherty Paul D.,Chiew Yeong-Shiong,Möller Knut,Chase J. Geoffrey

Funder

EU FP7

RSNZ Marie Curie IRSES funds

Health Research Council of New Zealand

University of Canterbury College Scholarships

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference34 articles.

1. Mechanical ventilation in ARDS: a state-of-the-art review;Girard;Chest,2007

2. Characteristics and outcomes in adult patients receiving mechanical ventilation: a 28-day international study;Esteban;JAMA: J. Am. Med. Assoc.,2002

3. Mechanical ventilation: lessons from the ARDSNet trial;Slutsky;Respir. Res.,2000

4. Effects of recruitment maneuvers in patients with acute lung injury and acute respiratory distress syndrome ventilated with high positive end-expiratory pressure;Brower;Crit. Care Med.,2003

5. Regional lung opening and closing pressures in patients with acute lung injury;Pulletz;J. Crit. Care,2012

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1. A Model-Based Quantification of Nonlinear Expiratory Resistance in Plethysmographic Data of Copd Patients;2024

2. How hard is it to breathe? Quantification of lung elastance and inspiratory work of breathing in healthy and COPD patients.;IFAC-PapersOnLine;2023

3. Model-based identification of flow-limited and non-flow-limited COPD patients in plethysmographic data.;IFAC-PapersOnLine;2023

4. An identifiable model of lung mechanics to diagnose and monitor COPD;Computers in Biology and Medicine;2023-01

5. Estimating the incidence of spontaneous breathing effort of mechanically ventilated patients using a non-linear auto regressive (NARX) model;Computer Methods and Programs in Biomedicine;2022-06

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