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Title: | Predicting Neurological Effects Associated with Traumatic Brain Injuries Using Video Analysis and Finite Element Modeling |
Authors: | Acot, Bianca "Gabbie" |
Advisors: | Glisic, Branko Dettwiler, Annegret Gilchrist, Michael |
Department: | Civil and Environmental Engineering |
Certificate Program: | Materials Science and Engineering Program |
Class Year: | 2021 |
Abstract: | The topic of concussions has become controversial due to the recent discoveries of long-term neurodegenerative diseases in former football players related to concussions occurred earlier in life. In order to prevent concussions, the mechanism of concussive head impacts in football must be understood. However, studying concussions is difficult because of the ethical issues related to concussion studies in live subjects. Finite element model simulations enable researchers to study the relation between predicted injury in the brain and head impact mechanics without live subjects. To improve the accuracy of these simulations, this paper developed a methodology to cyclically analyze and improve the process of finite element simulation of head impacts. Case studies of two college football players were analyzed through the following steps: video analysis of representative concussive hits to elucidate head impact mechanics, finite element simulation of head impact to garner biomechanical metrics in the brain, and correlation of biomechanical metrics with neuroimaging metrics. A relationship was found between these metrics but areas of improvement within the accident reconstruction and finite element simulation process were also found. Through acknowledging areas of further work, researchers can continue to develop the process of head impact simulations to eventually use this tool for diagnostic purposes. |
URI: | http://arks.princeton.edu/ark:/88435/dsp019g54xm76j |
Type of Material: | Princeton University Senior Theses |
Language: | en |
Appears in Collections: | Civil and Environmental Engineering, 2000-2023 |
Files in This Item:
File | Description | Size | Format | |
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ACOT-GABBIE-THESIS.pdf | 1.39 MB | Adobe PDF | Request a copy |
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