Non-invasive prediction of bloodstain age using the principal component and a back propagation artificial neural network

作者：Sun, Huimin; Meng, Yaoyong^*; Zhang, Pingli; Li, Yajing; Li, Nan; Li, Caiyun; Guo, Zhiyou

来源：Laser Physics Letters, 2017, 14(9): 095601.

DOI：10.1088/1612-202X/aa7c48

• whole blood
• Raman spectroscopy
• PCA
• BP-ANN
• forensics

The age determination of bloodstains is an important and immediate challenge for forensic science. No reliable methods are currently available for estimating the age of bloodstains. Here we report a method for determining the age of bloodstains at different storage temperatures. Bloodstains were stored at 37 degrees C, 25 degrees C, 4 degrees C, and -20 degrees C for 80 d. Bloodstains were measured using Raman spectroscopy at various time points. The principal component and a back propagation artificial neural network model were then established for estimating the age of the bloodstains. The results were ideal; the square of correlation coefficient was up to 0.99 (R-2 > 0.99) and the root mean square error of the prediction at lowest reached 55.9829 h. This method is real-time, non-invasive, non-destructive and highly efficiency. It may well prove that Raman spectroscopy is a promising tool for the estimation of the age of bloodstains.

• 出版日期2017-9
• 单位桂林医学院; 华南师范大学