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dc.contributor.authorMehrabi, Pouria
dc.contributor.authorHui, Justin
dc.contributor.authorMontazeri, Mahyar Mohaghegh
dc.contributor.authorNguyen, Kim Tien
dc.contributor.authorLogel, Abigail
dc.contributor.authorO'Brian, Allen
dc.contributor.authorHoorfar, Mina
dc.description.abstractDetection of volatile organic compounds (VOCs) in the exhaled breath is found to be a promising method to diagnose different diseases. The amount of alcohol or drugs absorbed/inhaled in the body can also be measured using gas sensors. Oral habits can affect the composition and also concentration of VOCs produced as a result of cellular metabolic reactions inside our body. Recognition of exhaled breath patterns including composition and concentration of VOCs provides useful information regarding how the breath affects the artificial olfaction systems. This can provide a powerful tool to calibrate gas sensors and detect VOCs associated with different diseases. In the following study, the breath signatures are extracted after different activities including fasting, brushing teeth, and drinking coffee. The results are normalized and implemented into a feature extraction model that extracts principal features for each regime. This will determine the breath signature of each regime. The results show that the effect of these activities on the breath is consistent between different subjects. This study provides the base signature of the exhaled breath which can be used in a clinical setting to identify other target VOCs that are considered the biomarkers of diseases.en_US
dc.rightsThe copyright for the paper content remains with the author.
dc.subjectBiomechanics and Biomedical Engineeringen_US
dc.subjectMicrotechnolgy and Nanotechnologyen_US
dc.subjectBreath analyzeren_US
dc.subjectGas sensoren_US
dc.subjectMicrofluidic artificial olfactionen_US
dc.titleSmelling Through Microfluidic Olfaction Technologyen_US

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