Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

Challenges, Strengths and Opportunities Related to Implementing Comprehensive Evidence-Based Guidelines on Breast Cancer Survivorship Care by Primary Care Physicians and Nurse Practitioners in Southeastern Ontario

Background Many breast cancer survivors continue to have a broad range of physical and psychosocial problems after breast cancer treatment. As cancer centres move forward with earlier discharge of stable breast cancer survivors to primary care follow-up it is important that comprehensive evidence-based breast cancer survivorship care is implemented to effectively address these needs. Research suggests primary care providers are willing to provide breast cancer survivorship care but many lack the knowledge and confidence to provide evidence-based care. Purpose The overall purpose of this thesis was to determine the challenges, strengths and opportunities related to implementing comprehensive evidence-based breast cancer survivorship guidelines by primary care physicians and nurse practitioners in southeastern Ontario. Methods This mixed-methods research was conducted in three phases: (1) synthesis and appraisal of clinical practice guidelines relevant to provision of breast cancer survivorship care within the primary care practice setting; (2) a brief quantitative survey of primary care providers to determine actual practices related to provision of evidence-based breast cancer survivorship care; and (3) individual interviews with primary care providers about the challenges, strengths and opportunities related to provision of comprehensive evidence-based breast cancer survivorship care. Results and Conclusions In the first phase, a comprehensive clinical practice framework was created to guide provision of breast cancer survivorship care and consisted of a one-page checklist outlining breast cancer survivorship issues relevant to primary care, a three-page summary of key recommendations, and a one-page list of guideline sources. The second phase identified several knowledge and practice gaps, and it was determined that guideline implementation rates were higher for recommendations related to prevention and surveillance aspects of survivorship care and lowest related to screening for and management of long-term effects. The third phase identified three major challenges to providing breast cancer survivorship care: inconsistent educational preparation, provider anxieties, and primary care burden; and three major strengths or opportunities to facilitate implementation of survivorship care guidelines: tools and technology, empowering survivors, and optimizing nursing roles. A better understanding of these challenges, strengths and opportunities will inform development of targeted knowledge translation interventions to provide support and education to primary care providers.