Training Considerations and Implementation of Robotic Assessments of Upper Limb Function in A Nonhuman Primate Model of Chronic Stroke

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Authors
Chen, Nancy
Keyword
Nonhuman primate , Chronic stroke , Robotic assessment
Abstract
During the development of potential stroke therapies, preclinical studies using animal models are crucial for evaluating safety and efficacy prior to human clinical trials. In designing preclinical studies, there are a number of experimental considerations that must be taken into account including selection of the appropriate animal model and method of stroke induction. These considerations depend critically both on the nature of therapy development and on the specific pathophysiological mechanism of damage that is being targeted. Despite published recommendations, preclinical stroke research is still a murky landscape without unifying methodologies on the assessment of behavioral or histological measures of outcome. The emergence of robotic forms of assessment and therapy could prove a useful tool for solving the problem of differing methodologies during behavioral assessment. Specifically, robotic technologies can be programmed to run certain tasks, and the motor movements of upper and lower limbs and the trunk recorded with high spatial and temporal resolution. Moreover, the same robotic assessments can also be performed on human subjects with ease, and functional outcomes as assessed by the same tasks compared between preclinical animal models of stroke and human stroke patients. Such studies could provide novel insight into behavioral and neural mechanisms underlying injury and recovery. The chapters of this thesis explore these topics and outline the feasibility, training, and ethical considerations of using a nonhuman primate model of chronic stroke and the characterization of motor deficits following ischemic stroke using robotic technologies. We first demonstrate that large numbers of animals can be trained to learn robotic assessment tasks in a timely manner. Subsequently, we show that robotic assessments of upper limb deficits in a visually guided reaching task following stroke are similar to those seen in human patients. Robotic assessments also reveal spasticity in contralesional elbows following injury. Lastly, we demonstrate that stroke affects the ability to counter externally applied postural perturbations. Taken together, these chapters demonstrate that assessing motor deficits in a nonhuman primate model of stroke using robotic technologies is a useful framework in which to test novel stroke therapies and interventions prior to human trials.
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