Terahertz time-domain spectroscopy (THz-TDS) systems are widely used to obtain fingerprint spectra of many different biomedical substances, and thus the identification of different biological materials, medicines, or dangerous chemicals can be realized. However, the spectral data for the same substance obtained from different THz-TDS systems may have distinct differences because of differences in system errors and data processing methods, which leads to misclassification and errors in identification. To realize the exact and fast identification of substances, spectral standardization is the key issue. In this paper, we present detailed disposal methods and execution processes for the spectral standardization and substance identification, including feature extracting, database searching, and fingerprint spectrum matching of unknown substances. Here, we take twelve biomedical compounds including different biological materials, medicines, or dangerous chemicals as examples. These compounds were analyzed by two different THz-TDS systems, one of which is a commercial product and the other is our verification platform. The original spectra from two systems showed obvious differences in their curve shapes and amplitudes. After wavelet transform, cubic spline interpolation, and support vector machine (SVM) classification with an appropriate kernel function, the spectra from two systems can be standardized, and the recognition rate of qualitative identification can be up to 99.17%.

中文翻译：

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基于太赫兹光谱的生物医学材料光谱标准化和定性鉴定方法

太赫兹时域光谱（THz-TDS）系统被广泛用于获取许多不同生物医学物质的指纹图谱，因此可以实现对不同生物材料，药物或危险化学品的识别。但是，由于系统误差和数据处理方法的差异，从不同的THz-TDS系统获得的同一物质的光谱数据可能会有明显的差异，这会导致分类错误和识别错误。为了实现准确，快速的物质识别，光谱标准化是关键问题。在本文中，我们介绍了光谱标准化和物质识别的详细处置方法和执行过程，包括特征提取，数据库搜索以及未知物质的指纹光谱匹配。这里，我们以十二种生物医学化合物为例，包括不同的生物材料，药物或危险化学品。这些化合物通过两种不同的THz-TDS系统进行了分析，其中一种是商业产品，另一种是我们的验证平台。来自两个系统的原始光谱显示出其曲线形状和幅度明显不同。经过小波变换，三次样条插值和支持向量机（SVM）分类并具有适当的核函数，可以对两个系统的光谱进行标准化，定性识别的识别率可以达到99.17％。其中一个是商业产品，另一个是我们的验证平台。来自两个系统的原始光谱显示出其曲线形状和幅度明显不同。经过小波变换，三次样条插值和支持向量机（SVM）分类并具有适当的核函数，可以对两个系统的光谱进行标准化，定性识别的识别率可以达到99.17％。其中一个是商业产品，另一个是我们的验证平台。来自两个系统的原始光谱显示出其曲线形状和幅度明显不同。经过小波变换，三次样条插值和支持向量机（SVM）分类并具有适当的核函数，可以对两个系统的光谱进行标准化，定性识别的识别率可以达到99.17％。