| Summary: | A single head impact in sport can cause an acute concussion, whereas repetitive head impacts are suspected to cause chronic neurological impairment. However, the diagnostic accuracy of concussion assessment tools are not well understood and sparse research evidence exists regarding the neurological implications of repetitive head impacts. The objective of this thesis was to investigate repetitive head impacts, including impact detection technology and neurocognitive function, over the duration of a collegiate football season. Thirty-five healthy participants were recruited from a collegiate football program for a three-part study. Participants adhered an impact detection sensor (xPatch, X2 Biosystems) to their right mastoid process prior to each game and practice. As well, they completed a weekly battery of neurological testing that included the graded symptom checklist, standardized assessment of concussion, balance error scoring system and King-Devick test. In experiment 1, we investigated the accuracy of the xPatch to classify each detected event as an impact or non-impact. We matched each event to game video and assigned a true positive, false positive, true negative or false negative classification. The sensitivity of the sensor was 77.6%, specificity was 70.4% and overall accuracy was 75.1%. Additionally, we determined that impact count is strongly correlated to cumulative head kinematic load, i.e. cumulative linear acceleration (r²=0.98), cumulative rotational acceleration (r²=0.98) and cumulative rotational velocity (r²=0.99). In experiment 2, we explored the relationship between alterations in neurological status and repetitive head impact exposure using linear mixed models. The number of head impacts sustained was significantly related to the number and severity of symptoms in participants, but not to any other indicator of neurological status. In experiment 3, we investigated the diagnostic accuracy of each neurological test using receiver operating characteristic curves and corresponding area under the curve values. The diagnostic accuracy for the graded symptom checklist was high (0.76-0.93), King-Devick Test was moderate (0.64-0.80), standardized assessment of concussion and balance error scoring system were poor (0.47-0.71). In summary, this thesis identified limitations in current impact detection technology, provided evidence of a link between repetitive head impacts and symptomatology, and determined that the graded symptom checklist can accurately diagnose concussion. === Education, Faculty of === Kinesiology, School of === Graduate
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