Library Dissertation Showcase

Comparing Methods of Simulating Backspatter from Cranial Gunshot Wounds

  • Year of Publication:
  • 2020

Backspatter is defined as blood drops traveling from the impact site of a blood source, against the direction of an applied external force. This type of bloodstain pattern is commonly seen in close-range cranial gunshots, and becomes key in reconstructing the events of a crime. Cranial models, like blood-soaked sponges, animals, or complex physical models, are commonly used in backspatter simulation experiments to generate spatter patterns to compare with those seen at a crime scene. Despite decades of application in the field, no cranial model has been validated for its accuracy in simulating a human head. Furthermore, existing research seeking to establish an accurate cranial model fails to test models under standardized parameters, and greatly lacks in the reporting of backspatter stain size distribution data. Results from these studies lack comparability with one another, hindering research efforts to establish a model’s simulation accuracy and the effects of changing shooting parameters, such as weapon type, caliber, and shooting distance. In this study, current literature was searched to compile two datasets: parameter data, exhibiting the most commonly tested parameters and gaps in current research, and secondary stain size distribution data, used to compare the backspatter patterns resulting from cranial models under various shooting parameters. Parameter data was compared to published case reports and used to determine a recommended standardized protocol for future backspatter simulation experiments. Secondary data was analyzed by Linear Mixed Model to evaluate the variation in spatter patterns between studies. Difference in data collection and reporting, rather than differences in shooting parameters, was found to be the greatest source of variance in spatter patterns. These results conclude future simulation experiments should follow the given recommendations for shooting parameters and data collection and analysis to enhance comparability between studies and enable the future validation of an accurate cranial model.

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