Stroke is the leading cause of disability in the U.S. The economic burden of stroke was estimated to be $30 billion in 1993, equal to 3% of national health expenditures. Much of that cost is due to the highly labor-intensive nature of present rehabilitation practice which suggests that it may be possible to use robotics and information technology to improve the productivity of the health care delivery expert and at the same time improve a stroke victim's quality of recovery. The broad goal of this research project is to use robotics to study stroke recovery and improve neuro-rehabilitation treatments. Current research into recovery from brain injury posits activity-dependent plasticity underlying neuro-recovery. That motivated the specific aims of this project, to (1) test whether sensory-motor activity facilitates significant recovery of motor function in patients recovering from stroke and (2) test whether recovered motor performance of stroke patients exhibits characteristics associated with normal motor learning. If true, this would provide a basis to adapt mathematical learning theories into a quantitative theory of motor recovery. Using robotics and information technology for neuro-rehabilitation will provide, for the first time, objective control and quantification of the motor activity delivered to a patient as well as precise and reliable measurement of patients' motor behavior, thus enabling a rigorous test of these hypotheses. Briefly, patients with stroke will receive standard post-acute hospital care in a defined stroke rehabilitation setting. Patients in the experimental group will also be given robot-administered training in the form of sensory-motor manipulation of their impaired upper limb. Outcomes will be measured using standard clinical instruments as well as novel robot-based measures. A follow-on study will test for evidence of specific behavioral features that may be characteristic of motor learning by comparing the recovered motor behavior and motor learning ability of out-patients with age-matched normal subjects. It is expected that results from this study will provide an objective basis for maximizing the benefits of at least this kind of (robot-administered) therapy; and may lay the groundwork for a quantitative theory of motor recovery and possible further refinements of neurologic rehabilitation. In the case of alternative outcomes it is expected that this systematic approach combined with the quality of robot-based measurements will contribute to a scientific foundation for neurologic rehabilitation.
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