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dc.contributor.authorSimmatis, Leifen
dc.date.accessioned2020-09-15T21:57:20Z
dc.date.available2020-09-15T21:57:20Z
dc.identifier.urihttp://hdl.handle.net/1974/28121
dc.description.abstractTransient ischemic attacks (TIA) are a substantial risk factor for ischemic stroke, but have been widely regarded as minor perturbations to the function of the central nervous system that leave little to no lasting impact on their own. However, in the last 20 years there has been a growing acceptance, that independent of increased risk of stroke, TIA can lead to neurological consequences that far outlast the previously prescribed symptom resolution window of 24 hours. The understanding of these deficits has been accelerated by the application of various technological approaches. Robotic assessment systems have been widely used to characterize neurological deficits arising from multiple sclerosis, Parkinson’s disease, and stroke. Their ability to measure motor behaviour precisely and reliably makes them ideal candidates to understand how TIA affects behaviour, and differs from other clinical conditions. In this thesis, the Kinarm robotic assessment system is used to characterize neurological deficits in people who have been diagnosed with TIA, and to understand how neurological deficits associated with TIA evolve over time. The objectives of this thesis were to: 1) characterize neurological deficits associated with TIA, and 2) describe change over time in impairments associated with TIA. It was demonstrated that approximately one third of individuals diagnosed with TIA displayed unexpected deficits in tests of motor ability, and up to half displayed impairments on tests of cognitive-motor integration. One-class, machine learning was then used for detecting abnormal behavioural patterns, and the performance of this approach was compared to our approach of statistically aggregating Kinarm task variables. The one-class approach led to fair detection of abnormal behavioural patterns, with the best model performance shown in tasks testing cognitive-motor integration (area under the receiver operating characteristic ~ 0.65), similar to the previous approach. In order to lay the groundwork for characterizing change over time, a statistical framework was provided for capturing changes in Kinarm robotic assessment performance after repeat tests. Finally, it was demonstrated that in people diagnosed with TIA the evolution of behavioural ability displays varying patterns; approximately 1/10 had perseveration of motor- and cognitive impairments for up to 1 year beyond symptom resolution. Together, these findings suggest that TIA is associated with lasting neurological impairments. The approaches outlined in this thesis may help pave the way for the identification of sensitive and specific behavioural biomarkers that could assist with the detection of TIA in clinically relevant settings.en
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectcerebrovascular disease, stroke, robotics, cognition, sensorimotor, motor, motor systemen
dc.titleRobotic Assessment to Detect Neurological Impairments Associated with Transient Ischemic Attacken
dc.typethesisen
dc.description.degreePhDen
dc.contributor.departmentNeuroscience Studiesen
dc.degree.grantorQueen's University at Kingstonen


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