Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure

The breathing dataset presented is collected from 20 healthy individuals at the University of Canterbury using a device to simulate the pressure and flow profiles of obstructive pulmonary disease. Specifically, the expiratory non-linear resistance, which generates the characteristic expiratory press...

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Main Authors: Jaimey A. Clifton, Ella F.S. Guy, Trudy Caljé-van der Klei, Jennifer L. Knopp, J. Geoffrey Chase
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340923009460
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author Jaimey A. Clifton
Ella F.S. Guy
Trudy Caljé-van der Klei
Jennifer L. Knopp
J. Geoffrey Chase
author_facet Jaimey A. Clifton
Ella F.S. Guy
Trudy Caljé-van der Klei
Jennifer L. Knopp
J. Geoffrey Chase
author_sort Jaimey A. Clifton
collection DOAJ
description The breathing dataset presented is collected from 20 healthy individuals at the University of Canterbury using a device to simulate the pressure and flow profiles of obstructive pulmonary disease. Specifically, the expiratory non-linear resistance, which generates the characteristic expiratory pressure-flow loop lobe seen in obstructive disease. Ethical consent for the trial was granted by the University of Canterbury Human Research Ethics Committee (Ref: HREC 2022/26/LR). Data was collected using an open-source data collection device connected to a Fisher and Paykel Healthcare SleepStyle SPSCAA CPAP. The trial was conducted at CPAP PEEP levels of 4 and 8 cmH2O, as well as at ZEEP (0 cmH2O) with no CPAP attached. The simulation device was a modular device connected to the expiratory pathway, consisting of a free volume diversion and fixed high resistance outlet. Three simulation levels were selected for testing, achieved by changing the size of the elastic free volume. The intended use of this dataset is for the initial validation and development of respiratory pulmonary mechanics models, using data collected from healthy people with simulated disease prior to clinical testing.
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spelling doaj.art-5ddcad56f28b4a6a834ed994fc57b58c2024-02-11T05:10:30ZengElsevierData in Brief2352-34092024-02-0152109903Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressureJaimey A. Clifton0Ella F.S. Guy1Trudy Caljé-van der Klei2Jennifer L. Knopp3J. Geoffrey Chase4Corresponding author.; Department of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New ZealandThe breathing dataset presented is collected from 20 healthy individuals at the University of Canterbury using a device to simulate the pressure and flow profiles of obstructive pulmonary disease. Specifically, the expiratory non-linear resistance, which generates the characteristic expiratory pressure-flow loop lobe seen in obstructive disease. Ethical consent for the trial was granted by the University of Canterbury Human Research Ethics Committee (Ref: HREC 2022/26/LR). Data was collected using an open-source data collection device connected to a Fisher and Paykel Healthcare SleepStyle SPSCAA CPAP. The trial was conducted at CPAP PEEP levels of 4 and 8 cmH2O, as well as at ZEEP (0 cmH2O) with no CPAP attached. The simulation device was a modular device connected to the expiratory pathway, consisting of a free volume diversion and fixed high resistance outlet. Three simulation levels were selected for testing, achieved by changing the size of the elastic free volume. The intended use of this dataset is for the initial validation and development of respiratory pulmonary mechanics models, using data collected from healthy people with simulated disease prior to clinical testing.http://www.sciencedirect.com/science/article/pii/S2352340923009460COPDPressureFlowPulmonary mechanicsSpirometryObstructive respiratory disease
spellingShingle Jaimey A. Clifton
Ella F.S. Guy
Trudy Caljé-van der Klei
Jennifer L. Knopp
J. Geoffrey Chase
Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
Data in Brief
COPD
Pressure
Flow
Pulmonary mechanics
Spirometry
Obstructive respiratory disease
title Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
title_full Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
title_fullStr Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
title_full_unstemmed Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
title_short Simulated obstructive respiratory disease dataset over increasing positive end-expiratory pressure
title_sort simulated obstructive respiratory disease dataset over increasing positive end expiratory pressure
topic COPD
Pressure
Flow
Pulmonary mechanics
Spirometry
Obstructive respiratory disease
url http://www.sciencedirect.com/science/article/pii/S2352340923009460
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