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Erschienen in: Journal of Clinical Monitoring and Computing 4/2016

16.07.2015 | Original Research

A mainstream monitoring system for respiratory CO2 concentration and gasflow

verfasst von: Jiachen Yang, Bobo Chen, Kyle Burk, Haitao Wang, Jianxiong Zhou

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 4/2016

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Abstract

Continuous respiratory gas monitoring is an important tool for clinical monitoring. In particular, measurement of respiratory \(\hbox {CO}_2\) concentration and gasflow can reflect the status of a patient by providing parameters such as volume of carbon dioxide, end-tidal \(\hbox {CO}_2,\) respiratory rate and alveolar deadspace. However, in the majority of previous work, \(\hbox {CO}_2\) concentration and gasflow have been studied separately. This study focuses on a mainstream system which simultaneously measures respiratory \(\hbox {CO}_2\) concentration and gasflow at the same location, allowing for volumetric capnography to be implemented. A non-dispersive infrared monitor is used to measure \(\hbox {CO}_2\) concentration and a differential pressure sensor is used to measure gasflow. In developing this new device, we designed a custom airway adapter which can be placed in line with the breathing circuit and accurately monitor relevant respiratory parameters. Because the airway adapter is used both for capnography and gasflow, our system reduces mechanical deadspace. The finite element method was used to design the airway adapter which can provide a strong differential pressure while reducing airway resistance. Statistical analysis using the coefficient of variation was performed to find the optimal driving voltage of the pressure transducer. Calibration between variations and flows was used to avoid pressure signal drift. We carried out targeted experiments using the proposed device and confirmed that the device can produce stable signals.
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Metadaten
Titel
A mainstream monitoring system for respiratory CO2 concentration and gasflow
verfasst von
Jiachen Yang
Bobo Chen
Kyle Burk
Haitao Wang
Jianxiong Zhou
Publikationsdatum
16.07.2015
Verlag
Springer Netherlands
Erschienen in
Journal of Clinical Monitoring and Computing / Ausgabe 4/2016
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-015-9739-y

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