Flow dependence of handheld breath analyzer for body fuel utilization monitoring
Issued Date
2023-01-01
Resource Type
ISSN
17426588
eISSN
17426596
Scopus ID
2-s2.0-85148029597
Journal Title
Journal of Physics: Conference Series
Volume
2431
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Physics: Conference Series Vol.2431 No.1 (2023)
Suggested Citation
Sricharoen C., Waritananta T., Wattanavicheana N., Jaisuthi R., Osotchan T. Flow dependence of handheld breath analyzer for body fuel utilization monitoring. Journal of Physics: Conference Series Vol.2431 No.1 (2023). doi:10.1088/1742-6596/2431/1/012017 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/82250
Title
Flow dependence of handheld breath analyzer for body fuel utilization monitoring
Author's Affiliation
Other Contributor(s)
Abstract
Home healthcare medical technologies have been gaining popularity and are more affordable in recent years. Exhaled breath analysis has potential in this field. The development of gas sensor technology has enabled us to build a small affable breath analysis device with the electronic nose concept. In this work, a handheld breath analyzer was developed for monitoring body fuel utilization. A hybrid gas sensor array, including electrochemical and photoacoustic gas sensors, was used to accurately measure oxygen and carbon dioxide in exhaled breath. The bypass configuration volume flow measurement method was developed to fit a small portable device. The experiment shows that both oxygen and carbon dioxide sensors are flow-dependent due to the slow response time of each sensor type. The response of the photoacoustic sensor is relatively slower than those of other sensor types. Thus, a mathematical model was developed to correct the individual sensor value to get a more accurate value of body fuel utilization. The comparison protocol of known concentrations of the oxygen and carbon gases with various flow conditions was conducted, and the mathematical model for reconstructing the original gas concentration was proposed. The result shows that the device is able to detect the RER change of humans after having a high carbohydrate content meal and after exercise