Bloodstain classification methods: A critical review and a look to the future


Emma Hook, Sarah Fieldhouse, David Flatman-Fairs, Graham Williams

Abstract

Classifying bloodstains is an essential part of Bloodstain Pattern Analysis. Various experts have developed methods. Each method considers the same basic bloodstain pattern types. These use either terminology based on the observable characteristics or the mechanistic cause of the bloodstain patterns as part of the classification process. This review paper considers ten classification methods from fourteen sources, which are used to classify bloodstain patterns. There are fundamental differences in how the patterns are classified, how differentiated the classification is, and whether the classification process uses clear, unambiguous criteria, and is susceptible to contextual bias. Experts have also reported issues with classifying bloodstains that have indistinguishable features. These differences expose key limitations with current classification methods: mechanistic terminology is too heavily relied on, and the classification process is susceptible to contextual bias. The development of an unambiguous classification method, based on directly observable characteristics within bloodstain patterns is recommended for future work.

Highlights
  • There are at least ten different methods to classify bloodstain patterns.
  • Most of the current methods are mechanistic and prone to contextual bias.
  • A lack of clearly defined, unambiguous classification criteria is a key limitation.
  • An unambiguous method for bloodstain classification resolves current limitations.
  • Further research in statistical descriptions and fluid dynamics is required.

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Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License which permits unrestricted noncommercial use, distribution, and reproduction, provided the original work is properly cited and not changed in any way.

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