In this study, the application of low-level fusion (LLF) and high-level fusion (HLF) strategies using a combination of Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy in the identification of antemortem and postmortem fracture at different postmortem intervals (PMIs) was investigated. On a technical level, the same hard tissue sample can be detected using a mix of FT-IR and Raman techniques. At the method level, two cutting-edge chemometrics approaches (LLF and HLF) combining FT-IR and Raman spectroscopic data are explored. The models were ranked in accordance with their parametric quality as follows: HLF and LLF + HLF models > LLF single model > Raman single model > FT-IR single model. The LLF model performed marginally better than the Raman model, however, when compared to other models, the HLF model performed considerably better. The HLF model achieved the best performance, with both cross-validation accuracy and test data set accuracy of 0.88. The importance of the feature wavelengths in the model construction process was subsequently evaluated by intersection fusion, and it was found that the absorbance bands of amide I, PO43– ν1 ν3, and CH2 in FT-IR and phenylalanine, CO32– ν1– PO43– ν3, and amide III in Raman have outstanding contributions to the construction of antemortem and postmortem fractures identification models. Overall, the combination of FT-IR and Raman with the HLF strategy is a novel and promising approach for developing antemortem and postmortem fracture identification models at different PMIs.

中文翻译：

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基于傅里叶变换红外光谱和拉曼光谱关联的低水平和高水平融合的生前和死后骨折识别协议

在这项研究中，结合傅里叶变换红外光谱（FT-IR）和拉曼光谱，应用低水平融合（LLF）和高水平融合（HLF）策略来识别不同死后的生前和死后骨折。研究了间隔（PMI）。在技​​术层面上，可以结合使用 FT-IR 和拉曼技术来检测相同的硬组织样本。在方法层面，探索了两种结合 FT-IR 和拉曼光谱数据的尖端化学计量学方法（LLF 和 HLF）。模型根据参数质量排序如下：HLF 和 LLF + HLF 模型 > LLF 单一模型 > 拉曼单一模型 > FT-IR 单一模型。LLF 模型的表现略好于拉曼模型，但是，与其他模型相比，HLF 模型的表现要好得多。HLF模型取得了最好的性能，交叉验证精度和测试数据集精度均为0.88。随后通过交叉融合评估了模型构建过程中特征波长的重要性，发现酰胺I、PO的吸收带43–ν1ν3、和CH2FT-IR 和苯丙氨酸，CO32–ν1– 采购订单43–ν3、拉曼中的酰胺III对生前和死后骨折识别模型的构建做出了突出的贡献。总体而言，将 FT-IR 和拉曼与 HLF 策略相结合是一种新颖且有前途的方法，用于开发不同 PMI 的生前和死后骨折识别模型。