Raman spectroscopy has proven to be a valuable tool for analyzing various types of forensic evidence such as traces of body fluids. In this work, Raman spectroscopy was employed as a nondestructive technique for the analysis of dry traces of oral fluid to differentiate between smoker and nonsmoker donors with the aid of advanced statistical tools. A total of 32 oral fluid samples were collected from donors of differing gender, age and race and were subjected to Raman spectroscopic analysis. A genetic algorithm was used to determine eight spectral regions that contribute the most to the differentiation of smokers and nonsmokers. Thereafter, a classification model was developed based on the artificial neural network that showed 100% accuracy after external validation. The developed approach demonstrates great potential for the differentiation of smokers and nonsmokers based on the analysis of dry traces of oral fluid.

中文翻译：

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基于口腔液的拉曼光谱和法医应用的高级统计信息，可区分吸烟者和非吸烟者。

拉曼光谱已被证明是分析各种法医证据（例如体液痕迹）的有价值的工具。在这项工作中，拉曼光谱法被用作一种无损技术，用于分析口腔液体的干痕迹，以借助先进的统计工具来区分吸烟者和非吸烟者。从不同性别，年龄和种族的供体中收集了总共32份口腔液样品，并进行了拉曼光谱分析。遗传算法用于确定八个光谱区域，这些区域对吸烟者和非吸烟者的区分贡献最大。此后，基于人工神经网络开发了分类模型，该模型在外部验证后显示出100％的准确性。