Robotics and related technologies have begun to realize their promise to improve the delivery of rehabilitation therapy. However, the mechanism by which they enhance recovery remains unclear. Ultimately, recovery depends on biology, yet the details of the recovery process remain largely unknown; a deeper understanding is important to accelerate refinements of robotic therapy or suggest new approaches. Fortunately, robots provide an excellent instrument platform from which to study recovery at the behavioral level. This article reviews some initial insights about the process of upper-limb behavioral recovery that have emerged from our work. Evidence to date suggests that the form of therapy may be more important than its intensity: muscle strengthening offers no advantage over movement training. Passive movement is insuffi-cient; active participation is required. Progressive training based on measures of movement coordination yields substantially improved outcomes. Together these results indicate that movement coordination ratherthan muscle activation may be the most appropriate focus for robotic therapy.

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This article describes the development of a mobile arm support for people with muscular diseases. The arm support is spring-balanced, with special attention on reduction of operating effort (high balancing quality and low friction), functionality (large range of motion), and aesthetics (inconspicuous design). The spring settings can be adjusted for wearing heavier clothing or picking up an object, a function that can also be used for moving up or down. The device levels itself automatically to compensate for uneven floors, a function that can be overruled to assist forward/backward motion of the arm. Thus, the balancer can compensate for the weight of the arm and be adjusted to generate force to a limited (safe) extent. The principle and design of the mechanism are presented and preliminary field trial results are given. Two users report on 6 months of continuous use of the arm support in their home and social environments.

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This research project focused on determining optimal power generation and distribution within a mobile human-scale power system. The intended application was for a human scale exoskeleton, in particular underwater applications. However, the tools and techniques are applicable for a broad range of mobile systems that carry a finite energy supply and need to optimize both the system performance and system efficiency. A wide survey of appropriate energy storage and power generation technologies was performed. Subsequently, a decision making algorithm was developed that specifically determined the best way to convert stored energy to available power coupled with the best way to distribute this power to multiple needs within the system. A dual stage decision making strategy was adopted whereby fast inner stage would determine both the needed power and the optimal control of the particular power application within the system. A slower second stage would accept the power demands from the first stage and then determine the optimal way generate that power from the stored energy source. The strategy was tested in simulation and experimentally. It was determined that a significant energy savings can be accomplished over conventional power management schemes while still achieving a particular mission’s performance requirements.

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