A novel, element-based approach for the objective classification of bloodstain patterns. (December 2015) - Arthur, Ravishka M.; Cockerton, Sarah L.; de Bruin, Karla G.; Taylor, Michael C.
Highlights: A novel approach for the classification of bloodstain patterns is proposed. Patterns are treated as a combination of discrete units termed elements. Mechanism-free terms are developed to describe the main features of a pattern. A classification system is devised and shown to be a useful visual tool. Characterising associations offers future potential for distinguishing patterns. Abstract: The classification of bloodstain patterns has been identified as a challenging part of bloodstain pattern analysis due to the lack of a widely accepted and well-defined methodology and the ambiguity often associated with examining bloodstain patterns. The main aim of this study was to develop an objective, science-based method, for classifying bloodstain patterns, through the development of common language that could be used by BPA experts to describe the appearance of the pattern. This novel approach encourages a shift in the mindset of a BPA analyst by bringing them 'back to the basics' by treating components of a bloodstain pattern as discrete, observable and measurable units. One of the principal problems with current pattern classification methods is that pattern types are generally described in terms of the mechanism of pattern formation rather than grouping according to observable pattern characteristics. This study extends current BPA classification methodologies by developing and validating mechanism-free nomenclature that arises from observing and documenting the physical characteristics of bloodstain patterns. Following the grouping of bloodstain components on the basis of their physical characteristics, the formation evolution of these components is then investigated using concepts drawn from the fluid-dynamics of bloodstain pattern formation. This study offers a promising approach to distinguishing between different bloodstain pattern types through the use of visual aids in the form of colour maps, high-speed video and static digital images.