Doctoral Dissertation Research: Multivariate Asymmetry and Allometry in Skeletal Elements for Osteometric Sorting

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

The problem of sorting human skeletal remains is encountered in bioarchaeological and forensic settings where the bones of multiple individuals are intermingled with no readily apparent indication as to which bone elements belong to which individual. Anthropologists use bone measurements to compare and match bones to single individuals, but current methods do not adequately account for the size and shape relationships between bones. This research project incorporates information on comparative bone morphology to create an automated sorting method. The expected product of this project will be a novel method that improves upon standard techniques, which would reduce the cost and increase the quality of results for bioarchaeological and forensic research. Sorting human remains is essential for aiding and streamlining medicolegal cases in the aftermath of mass fatalities and for returning deceased individuals to their loved ones. The project contributes to the training of a female graduate student with a strong commitment to diverse, inclusive science outreach efforts, and results of this study will be published in peer-reviewed journals, as well as presented at academic conferences. This project applies multivariate analyses of bilateral asymmetry and allometry to address the problem of osteometric sorting. Large data sets of bone measurements from archaeological and recent human populations will be evaluated to determine and characterize patterns of asymmetry and allometry in humans. Based on this information, novel methods will be developed for the sorting of mixed skeletal elements using bone measurements (osteometric sorting). This work will be done using the statistical and graphics package R, based on multivariate algorithms, such as Mahalanobis distance. This project will generate useful information about the morphological relationships between skeletal elements across different human populations and will result in the creation of an improved method for osteometric sorting. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.