To active rehabilitation training, Newton-Euler method is applied to build dynamic models for the powered exoskeleton and the subject. A method to extract the subject’s active force is proposed combined with the models. A mechanism for measuring the human-robot coupling force is designed on that basis. Two prototype experiments are proposed, one is an on-line experiment via different mass loadings, the other is the experiment via different forcing at rest positions in one gait cycle. The experimental results show that the mechanism is available for human-robot coupling force measuring. It also provides the feasibility and validity which will be used in subject’s on-line extracting of active forces based on the dynamic model during rehabilitation training.

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The distinguishing features of active exoskeletons are the capability of guiding arm movement at the level of the full kinematic chain of the human arm, and training full 3D spatial movements. We have specifically developed a PD sliding mode control for upper limb rehabilitation with gain scheduling for providing «assistance as needed», according to the force capability of the patient, and an automatic measurement of the impaired arm joint torques, to evaluate the hypertonia associated to the movement during the execution of the training exercise. Two different training tasks in Virtual Reality were devised, that make use of the above control, and allow to make a performance based evaluation of patient’s motor status. The PERCRO L-Exos (Light-Exoskeleton) was used to evaluate the proposed algorithms and training exercises in two clinical case studies of patients with chronic stroke, that performed 6 weeks of robotic assisted training. Clinical evaluation (Fugl-Meyer Scale, Modified Ashworth Scale, Bimanual Activity Test) was conducted before and after treatment and compared to the scores and the quantitative indices, such as task time, position/joint error and resistance torques, associated to the training exercises.

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This paper presents the analysis of three gait pattern adaptation algorithms applied to trajectory control of an exoskeleton for lower limbs. The proposed exoskeleton is based on a commercially available orthosis. The main dynamic characteristics of the orthosis-patient system are considered in MatLab and ADAMS simulations. Also, three gait-pattern adaptation algorithms are implemented considering the proposed model. These algorithms lead to a reduction of the estimated interaction forces between the human and the robot, allowing patients to change the gait-pattern according to their degree of voluntary locomotor capability. The first one is based on the inverse dynamics and minimizes a functional computed from interaction forces and orthosis-patient dynamics. In the second, based on the direct dynamics, the human-robot interaction forces are translated into a desired change in trajectory accelerations. The third one minimizes the interaction forces by controlling the impedance between the orthosis and the patient. Experimental joint trajectories obtained from the orthosis are considered as initial trajectories for the gait-pattern algorithms.

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A study was conducted to evaluate performance of a man-machine interface system consisting of a human wearing a passiveexoskeleton device. This experiment obtained some crude measures of human response characteristics treating the exoskeletondevice as a complicated sensor array. A Fitt’s law paradigm was used to help evaluate human performance. Fitt’s law is commonly used in human performance studies and it characterizes human response in terms of speed-accuracy tradeoffs that occur as humans perform tasks. Empirical data were collected during tests involving five subjects run using five levels of speed-accuracy tasks. The results are analyzed

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To automatically align exoskeleton axes to human anatomical axes, we propose to decouple the joint rotations from the joint translations. Decoupling can reduce setup times and painful misalignment forces, at the cost of increased mechanical complexity and movement inertia. The decoupling approach was applied to the Dampace and Limpact exoskeletons.

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