In recent years, the defining characteristics of cranial projectile trauma have
been reported extensively in experimental studies as well as forensic case
reports. The existing literature, however, focuses on trauma inflicted by
firearms, primarily handguns and rifles. Though firearms are the most
common form of projectile weapon used in a forensic context, there are
several types of projectile weapons which have not been examined through
experimental research. This gap in the literature not only limits the
examination of forensic cases, but also inhibits the examination of trauma
found within an archaeological context.
This study sought to differentiate the skeletal trauma caused by different
projectile weapons that are classified as either firearms (handgun, rifle, and
shotgun) or archery weapons (recurve hand bow with field tip arrows,
compound hand bow with fixed broadhead arrows, and compound crossbow
with field tip bolts, fixed broadhead bolts, and mechanical broadhead bolts).
Using polyurethane spheres as proxies for human cranial vaults, samples
were shot by one of the specified weapons (n=5) and 35 features resulting
from projectile impact (both qualitative and quantitative) of the entrance and
exit defects were recorded.
Using principal component analysis, it was found that the features of trauma
which accounted for the highest proportion of variance observed in the
subset which included both entry and exit defects were the maximum fracture
length on the external table of the entrance site, the minimum fracture length
on the external table of the entrance site, the entrance defect diameter, the
minimum fragment length of the fragments that originated from the entrance
defect, the width of the reconstructed exit defect, the maximum fracture
length on the external table of the entrance defect, and the width of the
reconstructed entrance defect. These accounted for 96.74% of the variance
within this dataset. When only examining the entrance defects, the most
distinguishing variables were the maximum fracture length on the external
table of the entrance defect, the width of the entrance defect, the minimum
fracture length on the external table of the entrance defect, and the width of
the reconstructed entrance defect, accounting for 95.89% of the variance
within this dataset.
Machine learning (linear discriminant analysis) was applied to test the
predictive strength of these variables. In testing the accuracy of these
predictions, it was found that the program could correctly predict the weapon
used for 74.19% of the samples when examining both the entrance and exit
defects and 60.87% of the samples when only examining the features of the
entrance defect.
The findings of this research exhibit the indiscernible qualitative features
between trauma inflicted by different projectile weapons, calling to attention
the need to change the current methods of weapon identification. This study
has established new quantitative methods for projectile trauma analysis
which are simple to perform, require minimal equipment, and are easily
applied to forensic and archaeological remains
