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.

Landfill Leachate Toxicity to Oncorhynchus mykiss (Rainbow Trout) at the Merrick Landfill

At the Merrick Landfill, located outside of North Bay (Ontario, CA), an investigation into the potential for an environmental impact to the Little Sturgeon River as a result of landfill leachate discharge was undertaken using toxicity testing using 96 hour acute lethality on Oncorhynchus mykiss (Rainbow Trout). Landfill leachate may present a risk to receiving environments as it is comprised of an array of chemicals including organics, ammonia, and metals. Testing was conducted in three phases, firstly testing was completed on site throughout an existing natural attenuation zone where the presence of several groundwater seeps down gradient of the site had been identified to determine the effectiveness of the existing leachate control features at reducing the environmental risks. These tests indicated that the existing capture strategies were largely effective at reducing toxicity risks to the receiving environment. Testing was also completed on two pilot-scale hybrid-passive treatment systems to determine their effectiveness for leachate treatment. Summer performance of a constructed gravel wetland system was also shown to be effective at reducing the toxicity of the landfill leachate at the site. Lastly in order to support evaluation of leachate treatment requirements, a toxicity identification evaluation (TIE) was performed to determine the principle cause of toxicity within the leachate. Based on water chemistry analyses of samples collected at various locations at the site, the TIE identified ammonia toxicity as the primary source of toxicity in the leachate, with a secondary focus on metal toxicity.