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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Stepping Beyond Behaviour: Explainable Machine Learning for Clinical Neurophysiological Assessment of Concussion Progression

Boshra, Rober January 2019 (has links)
The present dissertation details a sequence of studies in mild traumatic brain injury, the progression of its effects on the human brain as recorded by event-related electroencephalography, and potential applications of machine learning algorithms in detecting such effects. The work investigated data collected from two populations (in addition to healthy controls): 1) a recently-concussed adolescent group, and 2) a group of retired football athletes who sustained head trauma a number of years prior to testing. Neurophysiological effects of concussion were assessed across both groups with the same experimental design using a multi-deviant auditory oddball paradigm designed to elicit the P300 and other earlier components. Explainable machine learning models were trained to classify concussed individuals from healthy controls. Cross-validation performance accuracies on the recently-concussed (chapter 4) and retired athletes (chapter 3) were 80% and 85%, respectively. Features showed to be most useful in the two studies were different, motivating a study of potential differences between the different injury-stage/age groups (chapter 5). Results showed event-related functional connectivity to modulate differentially between the two groups compared to healthy controls. Leveraging results from the presented work a theoretical model of mild traumatic brain injury progression was proposed to form a framework for synthesizing hypotheses in future research. / Dissertation / Doctor of Philosophy (PhD)

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