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Application of Raman Spectroscopy for an Easy-to-Use, on-Field, Rapid, Nondestructive, Confirmatory Identification of Body Fluids

NCJ Number
239079
Author(s)
Igor K. Lednev
Date Published
February 2012
Length
80 pages
Annotation
This project developed a novel method for the non-destructive, confirmatory identification of body-fluid traces based on Raman spectroscopy combined with advanced statistics.
Abstract
The study showed the potential of Raman spectroscopy for the nondestructive, confirmatory identification of body-fluid traces, including stains on various substrates and contaminated mixtures. In addition, a program was developed for the automatic identification of body fluids in dry mixtures. The project confirmed the prior hypothesis that the Raman spectroscopic signature of each body fluid is unique and can be used for identification. A library of Raman signatures for blood, semen, vaginal fluid, saliva, and sweat was created, and software for the automatic identification of an unknown sample was developed. The method was expanded to include body-fluid stains on various substrates and contaminated stains. The project demonstrated that mixed samples of body fluids can be identified through automatic mapping if two body fluids are not thoroughly mixed. The dry traces of blood and semen were successfully identified on several substrates of practical importance. Human body fluids were collected from anonymous groups of donors, whose age, race, and gender were disclosed in order to ensure the required diversity and sample size. Samples of each body fluid were obtained from donors who represented five races. Drug traces of body fluids were tested using Raman microscope equipped with a computer-controlled stage for rapid mapping. A new approach to identification used multidimensional spectroscopic signatures to account for sample heterogeneity and variations with donor. The developed software algorithms compared experimental Raman spectra with the library of Raman signatures, providing quantitative measures of similarity. 23 figures, 6 tables, and 22 references
Date Published: February 1, 2012