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Title: Volatile urine biomarkers detection in type II diabetes towards use as smart healthcare application
Authors: Phuntsho Choden
Thara Seesaard
Tanthip Eamsa-Ard
Chutintorn Sriphrapradang
Teerakiat Kerdcharoen
Mahidol University
Keywords: Computer Science
Issue Date: 23-Mar-2017
Citation: 2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017. (2017), 178-181
Abstract: © 2017 IEEE. In this work, we fabricated six chemiresistive sensors, employed in a portable e-nose and performed tests with urine samples from two groups of population, namely type II diabetes and healthy subjects. To identify sensitivity and selectivity of chemiresistive gas sensors, the first test was performed towards five volatile organic compounds (VOCs) which are particularly found in human urine profiles and the second test with real urine samples from the volunteers. Principal component analysis (PCA) and cluster analysis (CA) applied to validate the obtained sensing response successfully spilt urinary volatile odors into two separate groups of diabetes and healthy status. A hypothesis testing (p-value approach) demonstrated that S3 and S4 (p0.05) responded specifically to the urine odors from diabetic patients and healthy subjects. Our findings suggest the possibility of using chemiresistive gas sensors in e-nose as an alternative diagnostic tool for diabetes detection through analysis of volatile urine odors.
Appears in Collections:Scopus 2016-2017

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