Smelling Through Microfluidic Olfaction Technology

Pouria Pouria, Justin Hui, Mahyar Mohaghegh Montazeri, K. T. Nguyen, Abigail Logel, Allen O'Brian, M. Hoorfar
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引用次数: 3

Abstract

Detection 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.
利用微流控嗅觉技术进行嗅觉
检测呼出气体中的挥发性有机化合物(VOCs)被认为是诊断不同疾病的一种很有前途的方法。人体吸收/吸入的酒精或药物的量也可以用气体传感器来测量。口腔习惯会影响体内细胞代谢反应产生的挥发性有机化合物的组成和浓度。识别呼气模式,包括挥发性有机化合物的组成和浓度,提供了有关呼吸如何影响人工嗅觉系统的有用信息。这可以为校准气体传感器和检测与不同疾病相关的挥发性有机化合物提供强大的工具。在接下来的研究中,在禁食、刷牙和喝咖啡等不同的活动后提取呼吸特征。将结果归一化并实现到特征提取模型中,该模型提取每个区域的主要特征。这将决定每一种呼吸方式的呼吸特征。结果表明,这些活动对呼吸的影响在不同的受试者之间是一致的。这项研究提供了呼气的基本特征,可用于临床环境,以识别被认为是疾病生物标志物的其他目标挥发性有机化合物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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