This paper proposes an augmented reality based exoskeleton for virtual object assembly training. This proposed hand exoskeleton consists of 9 DOF joints which can provide force feedback to all 5 fingers at the same time. This device has ability to simulate shape, size, and weight of the virtual objects. In this augmented reality system, user can assembly virtual objects in real workspace which is superimposed with computer graphics information. During virtual object assembly training, user can receive force feedback which is synchronized with physics simulation. Since this proposed system can provide both visual and kinesthesia senses, it will help the users to improve their assembly skills effectively.

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To make an accurate movement, the CNS has to overcome the inherent complexities of the multijoint limb. For example, interaction torques arise when motion of individual arm segments propagates to adjacent segments causing their movement without any muscle contractions. Since these passive joint torques significantly add to the overall torques generated by active muscular contractions, they must be taken into account during planning or execution of goal-directed movements. We investigated the role of the corticospinal tract in compensating for the interaction torques during arm movements in humans. Twelve subjects reached to visual targets with their arm supported by a robotic exoskeleton. Reaching to one target was accompanied by interaction torques that assisted the movement, while reaching to the other target was accompanied by interaction torques that resisted the movement. Corticospinal excitability was assessed at different times during movement using single-pulse transcranial magnetic stimulation (TMS) over the upper-arm region of M1 (primary motor cortex). We found that TMS responses in shoulder monoarticular and elbow–shoulder biarticular muscles changed together with the interaction torques during movements in which the interaction torques were resistive. In contrast, TMS responses did not correlate with assistive interaction torques or with co-contraction. This suggests that the descending motor command includes compensation for passive limb dynamics. Furthermore, our results suggest that compensation for interaction torques involves the biarticular muscles, which span both shoulder and elbow joints and are in a biomechanically advantageous position to provide such compensation.

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Current active leg prostheses do not integrate the most recent advances in Brain-Computer Interfaces (BCI) and bipedal robotics. Moreover, their actuators are seldom driven by the subject’s intention. In this paper, we propose an original and biologically-inspired leg prosthesis control scheme, which brings together these three aspects. It is composed of an EOG-based eye tracker and a Programmable Central Pattern Generator (PCPG). In a first step, specific sequences of eye movements executed by the user are identified by the eye tracking system. These sequences are then converted to high-level commands (such as accelerate, decelerate or stop) and sent to the prosthesis actuator control unit. In this unit, a PCPG is implemented, which is able to model human walk in a perfectly periodic way. One of the main interests of that tool is the possibility to modify the gait pattern to adapt to different walking speeds in a smooth way. Several results from previous studies are summarized and discussed in order to demonstrate the feasibility of such a system.

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In this paper, we propose a novel wearable sensor device for the measurement of the head orientation and relative position against the body trunk in real-time. It is known that in natural walking, human locomotion is preceded by changes in head orientation and the walking direction can therefore be predicted by observing the head orientation. We have been developing a wearable sensing device for the measurement of head orientation, which enables prediction of the future walking direction in real-time for the assistive technologies for locomotion — such as exoskeleton robots and wheelchair. Existing body posture measurement devices tend to be large and non-portable, therefore measurement in everyday space is still difficult. On the other hand, the developed system enables wireless and location independent measurement of the orientation of the head and it can be applied for assisted locomotion.

In evaluation of the accuracy of the developed device, we observed the head anticipation during natural walking. Additionally, we compared the head anticipation in natural walking and electric wheelchair locomotion using the developed device and discuss a novel wheelchair control based on head orientation.

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Safety is an important factor for human-machine interface devices. Brake actuated devices are potentially safer than those that rely on motors for force-feedback generation. However, manipulators using conventional frictional brakes do have limitations. This paper presents the experimental evaluation of a newly developed four-state rotary programmable brake in a 2DOF manipulator. The experimental results show improved performance compared to the results obtained when manipulators with conventional frictional brakes are used.

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