The virtual torque control is a relative effective control law for the lower extremity carrying exoskeleton robot, which needs no direct measurements from the pilot or the human-machine interface, but it needs the exact mass properties and its PD controller is not applicable for the serious nonlinear system. To overcome these defaults, the virtual prototyping software ADAMS is introduced to model the exoskeleton and the model is also used to the neural network (NN) dynamic mathematics model study. At the same time, the NN is used to the dynamic feed-forward controller to compensate the human-machine interaction force. Theoretical analyse and simulation results test the feasibility and validity of this control method.

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We have been developing an exoskeleton robot (ExoRob) for assisting daily upper limb movements (i.e., shoulder, elbow and wrist). In this paper we have focused on the development of a 2DOF ExoRob to rehabilitate elbow joint flexion/extension and shoulder joint internal/external rotation, as a step toward the development of a complete (i.e., 3DOF) shoulder motion assisted exoskeleton robot. The proposed ExoRob is designed to be worn on the lateral side of the upper arm in order to provide naturalistic movements at the level of elbow (flexion/extension) and shoulder joint internal/external rotation. This paper also focuses on the modeling and control of the proposed ExoRob. A kinematic model of ExoRob has been developed based on modified Denavit-Hartenberg notations. In dynamic simulations of the proposed ExoRob, a novel nonlinear sliding mode control technique with exponential reaching law and computed torque control technique is employed, where trajectory tracking that corresponds to typical rehab (passive) exercises has been carried out to evaluate the effectiveness of the developed model and controller. Simulated results show that the controller is able to drive the ExoRob efficiently to track the desired trajectories, which in this case consisted in passive arm movements. Such movements are used in rehabilitation and could be performed very efficiently with the developed ExoRob and the controller. Experiments were carried out to validate the simulated results as well as to evaluate the performance of the controller.

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This paper presents the preliminary results of the project BRAVO (Brain computer interfaces for Robotic enhanced Action in Visuo-motOr tasks). The objective of this project is to define a new approach to the development of assistive and rehabilitative robots for motor impaired users to perform complex visuomotor tasks that require a sequence of reaches, grasps and manipulations of objects. BRAVO aims at developing new robotic interfaces and HW/SW architectures for rehabilitation and regain/restoration of motor function in patients with upper limb sensorimotor impairment through extensive rehabilitation therapy and active assistance in the execution of Activities of Daily Living. The final system developed within this project will include a robotic arm exoskeleton and a hand orthosis that will be integrated together for providing force assistance. The main novelty that BRAVO introduces is the control of the robotic assistive device through the active prediction of intention/action. The system will actually integrate the information about the movement carried out by the user with a prediction of the performed action through an interpretation of current gaze of the user (measured through eye-tracking), brain activation (measured through BCI) and force sensor measurements.

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Stroke is very common and always leads to severe hand impairment. Traditional robotic systems have been introduced to assist therapy for a long time and already achieved certain effect. However, with further development of therapy strategies in the last few years, higher request to the rehabilitation robot has been put forward. Thus, we are developing a novel hand rehabilitation robot named HIT-glove to provide patient-cooperative therapy for hand-impaired post-stroke patients. In this paper, the mechanical design of the actuated hand exoskeleton is detailed and the control strategy for patient-cooperative therapy is introduced. The actuated hand exoskeleton, which can be applied to hands in different sizes and shapes, is able to bilaterally actuate every joint of the fingers. The patient-cooperative control strategy, based on the sensing system and an interactive interface, is well designed to let the patient actively participate into the therapy. Besides, to get a better effect of functional rehabilitation of the hand, our robot is expected to provide the following two categories of therapy: motor function exercise for joints and movement coordination training for fingers.

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This paper introduces a novel kinematic design paradigm for ergonomic human machine interaction. Goals for optimal design are formulated generically and applied to the mechanical design of an upper-arm exoskeleton. A nine degree-of-freedom (DOF) model of the human arm kinematics is presented and used to develop, test, and optimize the kinematic structure of an human arm interfacing exoskeleton. The resulting device can interact with an unprecedented portion of the natural limb workspace, including motions in the shoulder-girdle, shoulder, elbow, and the wrist. The exoskeleton does not require alignment to the human joint axes, yet is able to actuate each DOF of our redundant limb unambiguously and without reaching into singularities. The device is comfortable to wear and does not create residual forces if misalignments exist. Implemented in a rehabilitation robot, the design features of the exoskeleton could enable longer lasting training sessions, training of fully natural tasks such as activities of daily living and shorter dress-on and dress-off times. Results from inter-subject experiments with a prototype are presented, that verify usability over the entire workspace of the human arm, including shoulder and shoulder girdle

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