The development of new robotic devices for rehabilitation can lead to new and more efficient therapeutic procedures. Moreover, the use of VR-based scenarios in which patients perform rehabilitation exercises dramatically increases the patients¿ motivation and thus the final therapy outcome. In this paper preliminary results of a pilot study carried out with an exoskeleton for the robotic assisted rehabilitation of the upper limb are presented. The paper briefly describes the main kinematic and mechanical features of the exoskeleton system, showing its peculiar characteristics which make it useful for rehabilitation purposes. The implementation of three different robotic schemes of therapy in virtual reality with this exoskeleton, based on an impedance control architecture, are presented and discussed in detail. Finally, qualitative and quantitative results obtained in a 6 week pilot study with three chronic stroke patients are reported.

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We have been developing a 4DOF exoskeleton robot system in order to assist shoulder vertical motion, shoulder horizontal motion, elbow motion, and forearm motion of physically weak persons such as elderly, injured, or disabled persons. The robot is directly attached to a user’s body and activated based on EMG (electromyogram) signals of the user’s muscles, since the EMG signals directly reflect the user’s motion intention. A neuro-fuzzy controller has been applied to control the exoskeleton robot system. In this paper, controller adaptation method to user’s EMG signals is proposed. A motion indicator is introduced to indicate the motion intention of the user for the controller adaptation. The experimental results show the effectiveness of the proposed method.

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A new robotic exoskeleton for the upper-limb has been designed and constructed. Its primary purpose is to act as a proof-of-concept prototype for a more sophisticated rehabilitation and assessment device that is currently in development. Simultaneously, it is intended to extend the capabilities of an existing planar exoskeleton device. The robot operates in the horizontal plane and provides independent control of a user’s shoulder, elbow and wrist joints using a cable-driven actuation system. The novel component of the design is a curved track and carriage which allows the mechanism that drives the shoulder joint to be located away from the user, underneath their arm. This paper describes the design of the robot, and provides an initial indication of its performance.

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Brain-computer interface (BCI) research deals with establishing commu-nication pathways between the brain and external devices. BCI systems can be broadly classified depending on the placement of the electrodes used to detect and measure neurons firing in the brain: in invasive systems, electrodes are inserted directly into the cortex; in noninvasive systems, they are placed on the scalp and use electroencephalography or electrocorticography to detect neuron activity. This WTEC study was designed to gather information on worldwide status and trends in BCI research and to disseminate it to government decisionmakers and the research community. The study reviewed and assessed the state of the art in sensor technology, the bioticabiotic interface and biocompatibility, data analysis and modeling, hard-ware implementation, systems engineering, functional electrical stimulation, noninvasive communication systems, and cognitive and emotional neuroprostheses in academic research and industry. The WTEC panel identified several major trends in current and evolving BCI research in North America, Europe, and Asia. First, BCI research throughout the world is extensive, with the magnitude of that research clearly on the rise. Second, BCI research is rapidly approaching a level of first-generation medical practice; moreover, BCI research is expected to rapidly accelerate in nonmedical arenas of commerce as well, particularly in the gaming, automotive, and robotics industries. Third, the focus of BCI research throughout the world is decidedly uneven, with invasive BCIs almost exclusively centered in North America, noninvasive BCI systems evolving primarily from European and Asian efforts, and the integration of BCIs and robotics systems championed by Asian research programs. In terms of funding, BCI and brain-controlled robotics programs have been a hallmark of recent European research and technological development. The range and investment levels of multidisciplinary, multinational, multilaboratory programs in Europe appear to far exceed that of most university and government-funded BCI programs in the United States and Canada. Although several U.S. government programs are advancing neural prostheses and BCIs, private sources have yet to make a major impact on BCI research in North America generally. However, the U.S. Small Business Innovative Re-search grants (SBIRs) and Small Technology Transfer Research grants (STTRs) have been effective in promoting transition from basic research to precommercialized prototypes. In Asia, China is investing hea-vily in biological sciences and engineering in general, and the extent of investment in BCI and BCI-related research has grown particularly rapidly; still, the panel observed little coordination between various programs. Japanese universities, research institutes, and laboratories also are increasing their investment in BCI research. Japan is especially vigorous in pursuing nonmedical applications and exploiting its expertise in BCI-controlled robotics. The WTEC panel concludes that there are abundant and fertile opportunities for worldwide collaborations in BCI research and allied fields.

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Locomotor training using body weight support on a treadmill and manual assistance is a promising rehabilitation technique following neurological injuries, such as spinal cord injury (SCI) and stroke. Previous robots that automate this technique impose constraints on naturalistic walking due to their kinematic structure, and are typically operated in a stiff mode, limiting the ability of the patient or human trainer to influence the stepping pattern.We developed a pneumatic gait training robot that allows for a full range of natural motion of the legs and pelvis during treadmill walking, and provides compliant assistance. However, we observed an unexpected consequence of the device’s compliance: unimpaired and SCI individuals invariably began walking out-ofphase with the device. Thus, the robot perturbed rather than assisted stepping. To address this problem, we developed a novel algorithm that synchronizes the device in real-time to the actual motion of the individual by sensing the state error and adjusting the replay timing to reduce this error. This paper describes data from experiments with indi-viduals with SCI that demonstrate the effectiveness of the synchronization algorithm, and the potential of the device for relieving the trainers of strenuous work while maintaining naturalistic stepping.

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