Robotic gait rehabilitation is at least as effective as conventional gait training in stroke survivors. Patients must be assisted as needed in order to improve affected gait patterns. The combination of impedance control and series elastic actuation is a viable actuation principle to be used for human robot interaction. Here, a new promising electric series elastic actuated joint is developed. The large torque bandwidth limit at 100 Nm is 6.9 Hz. With a total weight of 3.175 kg it is possible to directly mount the actuator on the exoskeleton frame. The actuator is capable of providing sufficient torque at normal walking speed. Full patient assistance during gait and free motions without impeding the gait pattern are possible. The actuator allows isometric measurements up to 100 Nm and the patient’s progress in robotic rehabilitation can be evaluated.

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Task based repetitive therapy has been proposed to help stroke survivors to regain functional control of arm movement. We developed a wearable exoskeleton rehabilitation robot with associated control algorithm and safety protection mechanisms, and a graphic user interface that is easy to use and intuitive to patients and therapists, as the framework for automated and customizable robot-assisted rehabilitation system for clinic and home based therapy. The system was tested in two feasibility studies. The first study involved 6 patients to receive therapeutic training during three time weekly clinic visits for 4 weeks. The second study set up the robot-assisted rehabilitation system at patient’s house, where the therapeutic training was practiced on a daily base. Two patients were recruited for the home application study. Patients’ performances were assessed using clinical evaluation tools, including Wolf Motor Function Test and Fugl Meyer Assessment (FMA), both before and after the training. The performances of patients during the training weeks were also objectively evaluated by using the robot sensory data.

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The paper describes a new approach to image segmentation. It accepts the inherent deficiencies occuring when extracting low-level features and when dealing with the complexity of real scenes. Image segmentation therefore is understood as deriving a rich symbolic description useful for tasks such as stereo or object recognition in outdoor scenes. The approach is based on a polymorphic scheme for simultaneously extracting points, lines and segments in a topologically consistent manner, together with their mutual relations derived from the feature adjacency graph (FAG) thereby performing several grouping steps which gradually use more and more specific domain knowledge to achieve an optimal image description. The heart of the approach is (1) a detailed analysis of the FAG and (2) a robust estimation for validating the found geometric hypotheses. The analysis of the FAG, derived from the exoskeleton of the features, allows to detect inconsistencies of the extracted features with the ideal image model, a cell-complex. The FAG is used for finding hypotheses about incidence relations and geometric hypotheses, such as collinearity or parallelity, also between non-neighbored points and lines. The M-type robust estimation is used for simultaneously eliminating wrong hypotheses on geometric relationships. It uses a new argument for the weighting function

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Task based repetitive therapy has been proposed as a promising approach to train stroke survivors to regain functional control of arm movement. The hypothesis is that such intensive therapeutic approach can induce the desirable neural plasticity or adaptation to compensate for the damage in central nervous system. We have developed a wearable exoskeleton rehabilitation robot, the associated control algorithm, the framework for automated and customizable therapy sessions, safety protection mechanisms, and a graphic user interface that is easy to use and intuitive to the patients and therapists. The system was first tested in a laboratory setting on 6 stroke survivors on 3 weekly visits. Each patient went through a four-week period of robot assisted therapy. We then conducted at-home therapy for 2 subjects who used the system for arm function therapy at least once daily. Both the patients and the spouses are favorably impressed by this system setup, which stresses for training the arm movement according to a video game. After one week, they have already increased the practice intensity to twice a day with evidence of competency in motor control for more demanding tasks. The therapeutic effect of repetitive therapy will be best realized by long term and multiple intensive sessions per day. Such approach is feasible by robotic assisted setup at-home. Our approach will provide valuable information on determining therapy intensity and repetitions and monitoring progress.

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In order to assist the motion in the daily lives of physically weak persons such as elderly persons, many kinds of power-assist robots have been developed. In the case of some physically weak persons, the ability to perceive the environment is sometimes deteriorated also. A method of perception-assist has been proposed to assist not only the user’s motion but also the user’s interaction with an environment, by applying the modification force to the user’s motion if it is necessary. In this paper, the perception-assist for a lower-limb power-assist exoskeleton robot is proposed. In the daily life, the walking is very important for persons to achieve desired tasks. Basically, the robot assists the user’s muscle force according to the user’s motion intention which is estimated based on EMG signals. If the robot has found problems which might lead the user to dangerous situation such as the falling down, the robot tries to modify the user’s motion in addition to the ordinal power-assists to make the user walk properly. Since the user might fall down by the effect of the additional modification force of the perception-assist, the robot automatically prevents the user from falling down by considering ZMP (Zero Moment Point). The effectiveness of the proposed method has been evaluated by performing experiments.

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