Human vs non-human bone: identification and differentiation of fragmented skeletal remains using non-destructive methods

Date

2018

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Volume Title

Publisher

Cranfield University

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Type

Thesis

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Free to read from

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Abstract

Fragmented human and non-human bones can be found in forensic contexts, such as mass disasters, mass graves, and crime scenes, as well as in archaeological deposits. When fragmented skeletal remains are found, one of the first questions asked is whether or not the fragments are human or non- human. If none of the diagnostic features is visible, the origin of the fragments may be difficult to assess. Most of the methods currently employed to identify the origin of bone fragments, such as microscopic and biomolecular methods, are invasive and time consuming. The aim of the research presented in this thesis was to explore the potential of non-destructive procedures, such as GIS (Geographic Information System) software, morphological examination and Micro-Computed Tomography, in determining whether or not a bone fragment is human. These techniques were applied on skeletal features not commonly used for the human-nonhuman bone differentiation. Cranial suture patterns, cranial curvature and rib shaft curvature were assessed and measured using a GIS software. In addition, the morphology of the occipital condyles and the linea aspera of the femur were investigated and compared between human and non-human species. Finally, primary nutrient foramina and cross-sectional shape of long bones were analysed using micro-CT. More than 700 human and non-human bones were used; the non-human species selected are the ones whose remains are likely to be found in forensic or archaeological contexts in the United Kingdom. Most of the bone features considered and the procedures used in this study proved to be reliable for the differentiation between human and non-human fragmented bones. Blind tests performed on fragments whose human or non-human origin was not known further demonstrated the applicability and effectiveness of the methods and features explored in this study. The results of this research provide a valuable contribution to the fields of forensic anthropology, bioarchaeology, and comparative anatomy.

Description

© Cranfield University, 2018

Software Description

Software Language

Github

Keywords

Forensic anthropology, Micro Computed Tomography (MCT)

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© Cranfield University, 2018. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.

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