A number of rehabilitation robots were developed and used to promote the recovery of motor functions in the upper extremities of stroke patients. Current clinical evidence suggests that the robotic rehabilitation is much more effective in acute than in chronic patients. One important difference between the two groups is the amount of the baseline skills with which they start the training. The goal of our research was to get a further insight into this issue by conducting an experiment in healthy subjects. As a model of motor learning, simulating the process of robotic rehabilita-tion, we developed a methodology for the transfer of a motor skill from an expert to a novice subject by using a haptic interface integrated with the virtual environment. A motor skill was implemented in the form of a challenging computer game, and the haptic interface provided the assistive forces during playing. To assess if and how a level of prior skills affects the motor learning assisted by the robot, the game was played by both novice and partially trained players. The results showed that the assistance was effective only in the novice players, while the trained players experienced the assistive forces as a disturbance. In the context of neurorehabilitation, this finding implies that the existing experience of chronic patients, i.e., the established motor patterns (e.g., compensatory strategies), has to be considered when designing the assistance that would actually promote (instead of disturbing) the learning process.

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Устройство, представленное компанией Forcetek на крупнейшей выставке игровой индустрии E3, должно появиться в продаже уже в будущем году. Это далеко не первый игровой контроллер, управляющий персонажем, реагируя на активные движения игрока, сходные технологии уже предлагают все ведущие производители.

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This study proposes a lower-limb exoskeleton system that is controlled by a wearer’s muscle activity. This system is designed by following procedure. First, analyze the muscle activation patterns of human leg while walking. Second, select the adequate actuator to support the human walking based on calculation of required force of knee joint for step walking. Third, unit type knee and ankle orthotics are integrated with selected actuator. Finally, using this knee-assistive system (KAS) and developed muscle stiffness sensors (MSS), the muscle activity pattern of the subject is analyzed while he is walking on the stair. This study proposes an operating algorithm of KAS based on command signal of MSS which is generated by motion intent of human. A healthy and normal subject walked while wearing the developed powered-knee exoskeleton on his/her knees, and measured effectively assisted plantar flexor strength of the subject’s knees and those neighboring muscles. Finally, capabilities and feasibility of the KAS are evaluated by testing the adapted motor pattern and the EMG signal variance while walking with exoskeleton. These results shows that developed exoskeleton which controlled by muscle activity could help human’s walking acceptably.

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In this internship report the development of an impedance control method for an anthropomorphic lower extremity exoskeleton is described. This exoskeleton can be used to restore the gait of paralyzed people. Webots simulations are used to test the control method. Therefore a realis-tic model of both the human as the exoskeleton has to be made. The lower extremities of the human model have 6 DOF all in the sagital plane. The human model has only passive elements simulating that the human is fully paralyzed. The actuation is done by the exoskeleton. The human model is compared to a Matlab model of the TU Delft. The joint angle trajectories of both models are approximately the same. The exoske-leton model is anthropomorphic and is assumed to be rigidly at-tached to the user. The actuation is done directly at the joints, so that all sup-plied power is converted into joint rotation. The parameters of the impedance control, stiness, damping and reference trajectory, are phase dependent. They are determined using particle swarm optimization. The optimizations are able to find a gait pattern of the human model wearing the exoskeleton. This gait pattern is compared to the gait of a healthy subject, tracked by the University of Twente. The joint angles of the simulated gait have large similarities with the tracked angles. The developed model can be used to develop and test more complex control methods. By using a monotone fitness function and an adjusted fitness function the result can further improve.

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Previous studies have demonstrated that humans are sometimes capable of initiating arm movements towards visual stimuli at extremely short latencies, implying the presence of a short-latency neural pathway linking visual input to limb motor output. However, little is known about the neural mechanisms that underlie such hastened arm responses. One clue may come from recent demonstrations that the appearance of a visual target can elicit a rapid response in neck muscles that is time-locked to target appearance and functionally relevant for orienting gaze (head and eye) towards the target. Because oculomotor structures thought to contribute to ‘visual responses’ on neck muscles also target some arm muscles via a tecto-reticulo-spinal pathway, we hypothesized that a similar visual response would be present in arm muscles. Our results were consistent with this hypothesis as we observed the presence of rapid arm muscle activity (< 100 ms latency) that was time-locked to target appearance and not movement onset. We further found that the visual response in arm muscles: was present only when an immediate reach towards the target was required; had a magnitude that was predictive of reaction time; was tuned to target location in a manner appropriate for moving the arm towards the target; and was more prevalent in shoulder muscles than elbow muscles. These results provide evidence for a rapid neural pathway linking visual input to arm motor output and suggest the presence of a common neural mechanism for hastening eye, head and arm movements. (далее…)

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