No abstract

This study was designed to produce the first baseline measure of reliability in bloodstain pattern classification. A panel of experienced bloodstain pattern analysts examined over 400 spatter patterns on three rigid non-absorbent surfaces. The patterns varied in spatter type and extent. A case summary accompanied each pattern that either contained neutral information, information to suggest the correct pattern (i.e., was positively biasing), or information to suggest an incorrect pattern (i.e., was negatively biasing). Across the variables under examination, 13% of classifications were erroneous. Generally speaking, where the pattern was more difficult to recognize (e.g., limited staining extent or a patterned substrate), analysts became more conservative in their judgment, opting to be inconclusive. Incorrect classifications increased as a function of the negatively biasing contextual information. The implications of the findings for practice are discussed.

The analysis of bloodstain patterns can assist investigators in understanding the circumstances surrounding a violent crime. Bloodstains are routinely subjected to pattern analysis, which is inherently dependent upon the ability of the examiner to locate and visualize bloodstain patterns on items of evidence. Often, the ability to properly visualize bloodstain patterns is challenging, especially when the stain patterns occur on dark and/or patterned substrates. In this study, preliminary research was performed to better understand how near-infrared reflectance hyperspectral imaging (HSI) could be used to observe bloodstain patterns on commonly encountered black fabrics. The ability of HSI to visualize latent bloodstains on several commonly encountered substrates is demonstrated. The images acquired through HSI are of sufficient quality to allow for differentiation between stains produced from an impact mechanism or a transfer mechanism. This study also serves as a proof of concept in the differentiation of multiple staining materials. Because of its ability to generate spectral data, the data provide a preliminary separation of stains where more than one type of stain existed.

No abstract

This study was designed to produce the first baseline measure of the reliability of bloodstain pattern classifications on fabric surfaces. Experienced bloodstain pattern analysts classified bloodstain patterns on pairs of trousers that represented three fabric substrates. Patterns also varied in type (impact, cast-off, expiration, satellite stains from dripped blood, and transfer) and extent. In addition, case summaries that accompanied each pattern contained contextual cues that either supported the correct answer (i.e., positive bias), were misleading toward an incorrect answer (i.e., negative bias), or contained no directional information (i.e., neutral). Overall, 23% percent of the resulting classifications were erroneous. The majority (51%) of errors resulted from analysts misclassifying satellite stains from dripped blood. Relative to the neutral information, the positive-bias information increased correct classifications and decreased erroneous classifications, and the negative-bias information decreased correct classifications and increased erroneous classifications. The implications of these findings for BPA are discussed.