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: 1) study stroke recovery, and 2) optimize neuro-rehabilitation treatments. The working hypothesis is that there are at least two major aspects of neuro- recovery: 1) a process analogous to motor (re-)learning to compensate for damage to brain centers for coordination and control, and 2) a process analogous to recovery of strength and/or muscle tone.
The Specific Aims of this study are to understand and distinguish between the effects of rehabilitation to enhance recovery of sensori-motor coordination and rehabilitation to restore muscle tone, strength and the ability to move against gravity. Briefly, patients will be given conventional therapy and in addition, different forms of robot-administered therapy: some patients will receive """"""""placebo"""""""" therapy (in which the robot is inactive), others will receive sensori-motor training and others will receive progressive resistance exercise. Outcomes will be measured using conventional clinical instruments and also novel robot-based measures of coordination and muscle tone. Initial studies will focus on horizontal plane motions with the arm. Later studies will investigate motions against gravity, with and without robotic assistance. If the hypotheses are confirmed, it is expected that this study will provide an objective basis for: 1) maximizing the benefits of at least these two kinds of (robot-administered) therapy; 2) customizing this therapy to meet patients' specific needs; and 3) further refinements of robot neurologic rehabilitation. Should the hypotheses be falsified, it is expected that this systematic approach combined with the quality of robot-based measurements will contribute to the scientific foundations of neurologic rehabilitation.
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| Rohrer, Brandon; Hogan, Neville (2006) Avoiding spurious submovement decompositions II: a scattershot algorithm. Biol Cybern 94:409-14 |
| Hogan, Neville; Krebs, Hermano I; Rohrer, Brandon et al. (2006) Motions or muscles? Some behavioral factors underlying robotic assistance of motor recovery. J Rehabil Res Dev 43:605-18 |
| Volpe, Bruce T; Ferraro, Mark; Lynch, Daniel et al. (2005) Robotics and other devices in the treatment of patients recovering from stroke. Curr Neurol Neurosci Rep 5:465-70 |
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| Rohrer, Brandon; Fasoli, Susan; Krebs, Hermano Igo et al. (2004) Submovements grow larger, fewer, and more blended during stroke recovery. Motor Control 8:472-83 |
| Volpe, Bruce T; Ferraro, Mark; Lynch, Daniel et al. (2004) Robotics and other devices in the treatment of patients recovering from stroke. Curr Atheroscler Rep 6:314-9 |
| Fasoli, Susan E; Krebs, Hermano I; Hogan, Neville (2004) Robotic technology and stroke rehabilitation: translating research into practice. Top Stroke Rehabil 11:11-9 |
| Fasoli, Susan E; Krebs, Hermano I; Stein, Joel et al. (2004) Robotic therapy for chronic motor impairments after stroke: Follow-up results. Arch Phys Med Rehabil 85:1106-11 |
| Hogan, Neville; Krebs, Hermano I (2004) Interactive robots for neuro-rehabilitation. Restor Neurol Neurosci 22:349-58 |
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