Simultaneous assessment of volatile organic compound-based urinary and exhaled breath tests for diabetes diagnosis by using E-nose and VE-tongue systems

O. Zaim, Hafsa Elyoubi, N. E. Bari, B. Bouchikhi
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Abstract

Diabetes is a lifelong condition that may cause death and seriously affects the quality of life of a rapidly growing number of individuals. Thanks to their advantages, such as sensitivity, economic cost and ease of handling, the use of electrochemical devices could be very useful for the early, non-invasive and real-time diagnosis of diseases. The aim of this study is to compare breath and urine profiles of diabetes patients (DM) and healthy controls (HC) by using an electronic nose (E-nose) and a voltammetric electronic tongue (VE-tongue) combined with appropriate pattern recognition methods. The E-nose is based on five tin oxide (SnO2) sensors, while the VE-tongue consists of five metal electrodes. To this end, data gathered from both devices are treated by chemometric tools including principal component analysis (PCA), and discriminant function analysis (DFA) for easy visualization, interpretation and discrimination. As a result, PCA showed good discrimination between data-points of breath samples of DM patients and HC, with cumulative PCA scores of 98.17%. Furthermore, the DFA method revealed a clear separation among urine samples corresponding to DM patients and HC. Based on these results, the two proposed devices could be considered as a non-invasive tools for screening of diabetes diagnosis.
利用e -鼻和e -舌系统同时评估挥发性有机化合物为基础的尿液和呼气试验对糖尿病的诊断
糖尿病是一种可能导致死亡的终身疾病,严重影响越来越多的人的生活质量。由于其灵敏度、经济成本和易于操作等优点,电化学装置的使用对于疾病的早期、非侵入性和实时诊断非常有用。本研究的目的是通过使用电子鼻(E-nose)和伏安电子舌(VE-tongue)结合适当的模式识别方法,比较糖尿病患者(DM)和健康对照(HC)的呼吸和尿液特征。电子鼻基于5个氧化锡(SnO2)传感器,而ve舌则由5个金属电极组成。为此,从两个设备收集的数据通过化学计量学工具进行处理,包括主成分分析(PCA)和判别函数分析(DFA),以便于可视化,解释和区分。因此,PCA对DM患者和HC患者呼吸样本数据点具有较好的判别性,累积PCA得分为98.17%。此外,DFA方法显示DM患者和HC患者对应的尿液样本之间存在明显的分离。基于这些结果,这两种装置可以被认为是筛查糖尿病诊断的非侵入性工具。
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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