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A Stroke can affect different parts of the human body depending on the area of brain effected; our research focuses on upper limb motor dysfunction for stroke patients. In current practice, ordinal scale systems are used for conducting physical assessment of upper limb impairment. The reliability of these assessments is questionable, since their coarse ratings cannot reliably distinguish between the different levels of performance. This thesis describes the design, implementation and evaluation of a novel system to facilitate stroke diagnosis which relies on data collected with an innovative KINARM robotic tool. This robotic tool allows for an objective quantification of motor function and performance assessment for stroke patients. The main methodology for the research is Case Based Reasoning (CBR) - an effective paradigm of artificial intelligence that relies on the principle that a new problem is solved by observing similar, previously encountered problems and adapting their known solutions. A CBR system was designed and implemented for a repository of stroke subjects who had an explicit diagnosis and prognosis. For a new stroke patient, whose diagnosis was yet to be confirmed and who had an indefinite prognosis, the CBR model was effectively used to retrieve analogous cases of previous stroke patients. These similar cases provide useful information to the clinicians, facilitating them in reaching a potential solution for stroke diagnosis and also a means to validate other imaging tests and clinical assessments to confirm the diagnosis and prognosis. / Thesis (Master, Computing) -- Queen's University, 2008-09-27 11:14:04.85

The contribution of deficits in limb position sense to the motor impairments of children with cerebral palsy, as well as other neurodevelopmental disorders, is increasingly being recognized. A more complete understanding of the development of multi-joint upper limb position sense is needed and has been limited, to date, by the absence of a reliable measurement technique to produce clinically meaningful information. The KINARM Exoskeleton’s bilateral position matching task, which involves passive movement of one of the subject’s arms to one of eight positions requiring different combinations of elbow and shoulder positions and active matching by the participant’s other arm, was evaluated for interrater and retest reliability. Intraclass correlation coefficients, absolute difference, minimum detectable difference that would be considered a significant change in performance, standard error of the measure, coefficient of variation, index of reliability, limit of agreement and confidence intervals were used to determine reliability on three measures of multi-joint position sense: (1) inter-trial variability in end-point position, (2) the ratio between actual and matched position, or spatial contraction/expansion, which provides a measure of the absolute accuracy of position matching, and (3) systematic errors in matching. Interrater index of reliability was very good to excellent with values of 72% for systematic errors in matching to 93% for contraction/expansion. Interrater intraclass correlation values were fair to excellent at 0.46 for systematic errors in matching to 0.81 for contraction/expansion. Standard errors in measurement were low and ranged from 0.002 to 0.06, for inter-trial variability and contraction/expansion respectively. Similarly, minimal detectable difference values for retest reliability ranged from 0.005 for inter-trial variability to 0.161 for contraction/expansion. Retest intraclass correlation values were fair to excellent at 0.38 for systematic errors in matching to 0.82 for contraction/expansion. Moderate to strong interrater and retest reliability and high measurement precision support the use of robot-based assessment of multi-joint position sense for developmental studies and promises to be a reliable clinical and research tool in the advancement of knowledge on sensory-motor coordination difficulties in children with neurodevelopmental disorders. / Thesis (Master, Rehabilitation Science) -- Queen's University, 2011-09-29 05:43:47.255