In recent years, robot-assisted rehabilitation systems have been an active research area that can quantitatively monitor and adapt to patient progress, and ensure consistency during rehabilitation. In this work, an exoskeleton type robot-assisted rehabilitation system called RehabRoby is developed. A control architecture, which contains a high level controller and a low level controller, is designed for RehabRoby. Proprioceptive sense of healthy subjects has been evaluated during the execution of a task with RehabRoby. Additionally, usability of RehabRoby has been evaluated using a questionnaire.

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This paper presents a virtual reality-enhanced hand rehabilitation support system with a symmetric master-slave motion assistant for independent rehabilitation therapies. This system consists of a hand exoskeleton device and a lateral symmetric master-slave motion assistant system joined with a virtual reality (VR) environment. Since most disabilities caused by cerebral vascular accidents or bone fractures are hemiplegic, we adopted a symmetric master-slave motion assistant system in which the impaired hand is driven by the healthy hand on the opposite side. Furthermore, a VR environment displaying an enjoyable exercise was introduced. To verify the effectiveness of this system, a clinical trial was executed using one subject.

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Exoskeletal devices can provide assistance and supplement to the biological musculoskeletal members. We present a wearable robotic exoskeleton conceived as an improved lower leg orthosis for compensation of human knee and ankle joints disorders provoked by muscle weaknesses during walking, introducing novel biomechanical and user acceptance aspects and daily performance monitoring functionalities.

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This paper details the development of a virtual simulation tool for serial manipulators in the Python language (PyMani). PyMani uses a modular design to increase the ease of learning and future development. It was used to test a design for an upper-limb assistive exoskeleton robot with seven degrees of freedom (DoF). Future work will focus on creating additional features, the code is open source and available at sourceforge

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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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