Different gait patterns of stroke patients cannot be derived satisfactorily by traditional treadmill training robots. This paper presents a method to generate adaptive trajectories for controlling a lower extremity rehabilitation exoskeleton designed to help patients recover or improve walking ability. The model-based adaptation mechanism that consists of an inverse dynamic model, a trajectory generator and a fuzzy adaptation algorithm is proposed to minimize patient’s discomfort when active muscle contractions are not easily to be obtained. The effectiveness of the fuzzy adaptation algorithm, which accounts for the experience of a rehabilitation doctor, is demonstrated numerically with an illustrative example in this paper.

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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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This paper presents a method taking advantage of medically available MRI (Magnetic Resonance Imaging) data to derive the kinematics of a knee joint. The bio-joint model is applied to the design of a compliant sensing mechanism with two examples. The first investigates the effect of materials and characteristic geometry of the compliant mechanism on the knee joint, while the second (utilizing the bio joint model as boundary conditions to measure the knee joint rotation and internal forces involved) provides a better understanding on the interaction between the human knee and compliant sensing mechanism. The results potentially help establish a new topic of accommodating human bio-joint variations and nature degrees-of-freedom movements in the design of an exoskeleton.

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Parallel robots find many applications in human-systems interaction, medical robots, rehabilitation, exoskeletons, to name a few. These applications are characterized by many imperatives, with robust precision and dynamic workspace computation as the two ultimate ones. This paper presents a multi-objective optimum design procedure to 3 degrees of freedom (DOF) parallel robots with regards to four optimality criteria: workspace boundary, transmission quality index, stiffness. A kinematic optimization was performed to maximize the workspace of the parallel robot. In order to perform an optimal design of 3 DOF parallel robots, an objective function was developed first, and then Genetic Algorithms applied in order to optimize the objective function. The experimental results demonstrate the advantages of the presented optimization procedure in design of 3 DOF parallel robots, specifically TRIGLIDE and DELTA robots. These advantages are reflected in a presented framework for robust, precise, and dynamically calculated workspace boundaries. Therefore, the performances of the 3 DOF translation parallel robots provide high potential and good prospects for their practical implementation in human-systems interaction.

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The principal goal of this work is the development, testing and experimentation of a device for the hand rehabilitation. The system we designed is intended for people who have partially lost the ability to control correctly the hand musculature, for example after a stroke or a spinal cord injure. Based on EMG signals the system can «understand» the subject volition to move the hand and thanks to its actuators can help the fingers movement in order to perform the task. In this paper we describe the device and discuss the first results conducted on a healthy volunteer.

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