Colorimetric analysis of saliva-alcohol test strips by smartphone-based instruments using machine-learning algorithms

Kim Huisung; Awofeso Olumide; Choi Somi; Jung Youngkee; Bae Euiwon

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Colorimetric analysis of saliva-alcohol test strips by smartphone-based instruments using machine-learning algorithms

机译：采用机器学习算法的智能手机仪器对唾液醇试验条比色分析

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We report a smartphone-based colorimetric analysis of saliva-alcohol concentrations, utilizing optimal color space and machine-learning algorithms. Commercial saliva-alcohol kits are used as a model experiment, utilizing a custom-built optical attachment for the smartphone to obtain consistent imaging of the alcohol strips. The color of the strips varies with the alcohol concentration, and the smartphone camera captures the color produced on the test strip. To make a suitable library for each alcohol concentration, statistical methods were tested to maximize between-scatter and minimize within-scatter for each concentration. Results of three different classification methods (LDA, SVM, and ANN) and four-color spaces (RGB, HSV, YUV, and Lab) were evaluated with various machine-learning data sets and five different smartphone models. Cross-validation results were used to assess the statistical performance, such as positive (PPV) and negative (NPV) predictive values. An Android app developed and provided average classification rates of 100% and 80% for the standard and enhanced concentrations, respectively. (C) 2016 Optical Society of America

机译：我们报告了一种基于智能手机的比色分析唾液醇浓度，利用最佳颜色空间和机器学习算法。商用唾液醇试剂盒用作模型实验，利用用于智能手机的定制光学附件，以获得醇条的一致成像。条带的颜色随酒精浓度而变化，智能手机相机捕获测试条上产生的颜色。为了使每个醇浓度制备合适的文库，测试统计学方法以最大化 - 散射之间的散射和最小化散射率。使用各种机器学习数据集和五种不同的智能手机模型评估了三种不同分类方法（LDA，SVM和ANN）和四色空间（RGB，HSV，YUV和实验室）的结果。交叉验证结果用于评估统计性能，例如正（PPV）和负（NPV）预测值。 Android应用程序分别开发并提供了标准和增强浓度的平均分类率为100％和80％。（c）2016年美国光学学会

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《Applied optics》 |2017年第1期|共9页
作者
Kim Huisung; Awofeso Olumide; Choi Somi; Jung Youngkee; Bae Euiwon;
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Purdue Univ Sch Mech Engn Appl Opt Lab W Lafayette IN 47907 USA;

Purdue Univ Sch Mech Engn Appl Opt Lab W Lafayette IN 47907 USA;

Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA;

Purdue Univ Sch Mech Engn Appl Opt Lab W Lafayette IN 47907 USA;

Purdue Univ Sch Mech Engn Appl Opt Lab W Lafayette IN 47907 USA;

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正文语种 eng
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Colorimetric analysis of saliva-alcohol test strips by smartphone-based instruments using machine-learning algorithms

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