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

Abstract

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 °C, 25 °C, 4 °C, and −20 °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 (R2 > 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.