Data · dataset · 2023
Respiratory pressure and split flow data collection device with rapid expiratory shuttering
Listed in Teesside University Research Data Repository
The venturi-based flow meter utilises split inspiratory and expiratory flow pathways, for greater configurability with additional respiratory monitoring or simulation devices, as well for ease of data processing.
Description
The venturi is designed to be integrated in series with respiratory circuitry, using standard 22mm male and female connections. In its current application the inspiratory input port (22mm male connection) is connected to a CPAP device using its accompanying circuitry (or is unconnected when CPAP is not required), the expiratory output port vents to atmosphere (22mm female connection), and the subject port (22mm male connection) is connected to a mouthpiece, filter, or mask.
Differential Pressure Sensors were also upgraded (SSCDRRN001PD2A5) to capture larger flow ranges (seen in maximal breaths and panting). Additionally, a modular expiratory shutter attachment is outlined for identification of passive respiratory mechanics. Specifically, the rapid expiratory shuttering allows for breath-wise identification of elastance and resistance during shutter instances.
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Thus, eliminating the issue of trade-off associated with the simultaneous fitting of elastance and resistance to expiratory profiles. Ultimately, the device provides researchers with: - Rapid expiratory occlusion for identification of passive lung mechanics - A low-cost alternative to commercial sensor systems - Individual inspiratory and expiratory flow pathways - Non-invasive data collection - A modular design with high customisability
Links
Where it is published
- DOI doi.org/10.17632/7mshy2kcf3.3 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Biomedical engineering · Earth & Environmental Science · Engineering
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/7mshy2kcf3.3 | 8 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4003 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Biomedical Engineering'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |