Methodologies Applied to Fingerprint Analysis

J Forensic Sci. 2020 Jul;65(4):1040-1048. doi: 10.1111/1556-4029.14313. Epub 2020 Mar 16.

Abstract

This systematic review deals with the last 10 years of research in analytical methodologies for the analysis of fingerprints, regarding their chemical and biological constituents. A total of 123 manuscripts, which fit the search criteria defined using the descriptor "latent fingermarks analysis," were selected. Its main instrumental areas (mass spectrometry, spectroscopy, and innovative methods) were analyzed and summarized in a specific table, highlighting its main analytical parameters. The results show that most studies in this field use mass spectrometry to identify the constituents of fingerprints, both to determine the chemical profile and for aging. There is also a marked use of mass spectrometry coupled with chromatographic methods, and it provides accurate results for a fatty acid profile. Additional significant results are achieved by spectroscopic methods, mainly Raman and infrared. It is noteworthy that spectroscopic methods using microscopy assist in the accuracy of the analyzed region of the fingerprint, contributing to more robust results. There was also a significant increase in studies using methods focused on finding new developers or identifying components present in fingerprints by rapid tests. This systematic review of analytical techniques applied to the detection of fingerprints explores different approaches to contribute to future studies in forensic identification, verifying new demands in the forensic sciences and assisting in the selection of studies for the progress of research.

Keywords: forensic identification; forensic science; latent fingermarks; latent fingerprints; mass spectrometry; nanoparticles; spectroscopy.

Publication types

  • Systematic Review

MeSH terms

  • Chromatography
  • Dermatoglyphics*
  • Fatty Acids / chemistry
  • Forensic Sciences / methods*
  • Humans
  • Immunoassay
  • Lipids / chemistry
  • Mass Spectrometry
  • Nanoparticles
  • Spectrum Analysis
  • Time Factors

Substances

  • Fatty Acids
  • Lipids