THE IMPACT OF CORRELATIONS IN CONSOLIDATING STANDARDIZED ROBOTIC TASKS INTO A GLOBAL PERFORMANCE SCORE
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Authors
Fleury, Colleen
Date
Type
thesis
Language
eng
Keyword
Kinarm , Correlations , Monte Carlo , Neuroscience , primary outcome
Alternative Title
Abstract
Neurological diseases and disorders that impact the brain contribute a considerable
amount to global burden of disease. Informative assessment is needed to guide treatment and
identify novel interventions. However, clinically used neurological scales are coarse and
commonly have floor and ceiling effects, impacting their suitability for clinical trials.
Kinematic-based measures using technologies such as interactive robots possess the fine
resolution to detect improvements in motor function and may prove useful to quantify the
potential benefits of novel therapeutic interventions. Our lab has developed over a dozen robot based behavioral tasks to quantify sensory, motor, and cognitive function associated with the
arm. Detailed spatiotemporal measures are combined to provide a single measure of performance
in the task, called a Task Score. The challenge is to combine these Task Scores into a single
measure suitable for use in clinical trials.
The present thesis explores how Tasks Scores can be combined to create a single measure
of overall performance, called the Kinarm Score. While a simple summation of Tasks Scores
could be used, the presence of correlations across behaviours may impact the ability to identify
impairments. Notably, the use of actual healthy participant data to compute these correlations
would require all participants to complete all robot-based tasks whenever a new task is
developed. Thus, the addition of one new task requires hundreds of individuals to be assessed.
First, simulations were used to quantify how correlations across Tasks Scores would
impact a global Kinarm score. We found that with a moderate correlation of 0.6, the number of
individuals classified as impaired was 6.86% (± 0.55%), rather than the expected level of 5%.
Importantly, each additional task increased this error such that 9 tasks increased the percentage
of impaired individuals to 15.5% (± 1.02%), more than 3 times the expected level.
Next, techniques were developed to incorporate correlations into a simulated dataset. The
inclusion of inter-task correlations improved model performance by identifying only 6.7% of
individuals as impaired in contrast to the 10% if correlations were not considered in the
simulated dataset (5% is expected).
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Copying and Preserving Your Thesis
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ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This 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.