In this paper, a grip amplified glove using pneumatic artificial rubber muscles (PARMs) which are covered with a exoskeletonstructure is developed. A bi-articular mechanism with a PARM that is suitable for bending finger is realized. The glove has totally 10 DOFs consist of four units. To achieve power-assist motion properly, the PI control, which is based on the pressure value from the balloon sensor, is performed. This sensor makes the applied part free from electricity. To evaluate the validity of glove, the skin surface electromyography (EMG) signals of muscles are measured during grasping. These results demonstrate that the effectiveness of the power amplified glove.

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One of the key requirements for a Virtual Reality system is the multimodal, real-time interaction between the human operator and a computer simulated and animated environment. This paper investigates problems related particularly to the haptic interaction between the human operator and a virtual environment. The work presented here focuses on two issues: 1) the synthesis of whole-hand kinesthetic feedback, based on the application of forces (torques) on individual phalanges (joints) of the human hand, and 2) the experimental evaluation of this haptic feedback system, in terms of human haptic perception of virtual physical properties (such as the weight of a virtual manipulated object), using psychophysical methods. The proposed kinesthetic feedback methodology is based on the solution of a generalized force distribution problem for the human hand during virtual manipulation tasks. The solution is computationally efficient and has been experimentally implemented using an exoskeleton force-feedback glove. A series of experiments is reported concerning the perception of weight of manipulated virtual objects and the obtained results demonstrate the feasibility of the concept. Issues related to the use of sensory substitution techniques for the application of haptic feedback on the human hand are also discussed.

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Robot-assisted rehabilitation is an active area of research in the field of stroke rehabilitation. RUPERT is a wearable roboticexoskeleton powered by pneumatic muscle actuators. In this study, we described the structure of the controllers for the five degrees of freedom currently used by RUPERT. We applied the RUPERT on 6 stroke patients to provide robot-assisted rehabilitation therapy in a clinical study. Statistical χ² test on the proportion of successfully reaching targets showed that 3 out of the 6 patients demonstrated significant improvement in reaching targets successfully, and the remaining 3 did not show performance improvement or deterioration. We plan to implement the RUPERT in the patient’s house for easier access and more frequent use. More significant performance results are expected.

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The Wilmington Robotic Exoskeleton (WREX) is a passive upper limb orthosis powered by elastic bands, designed to assist children with weakness in their upper limbs. Patient studies with the WREX have determined that an external power source would enhance performance of the system. Two actuation schemes were considered: (i) motors in series with springs at the joints, called `Torsional’ (ii) motors in series with gravity balancing elastic bands, called `In-line’. Dynamic models of these two motor placements were developed. Dynamic simulations, based on representative patient motion data, were performed. We observed that the torsional case with motors in series with springs at the joints required substantially less torque when compared to the in-line case with motors in series with gravity balancing springs. An experimental platform is being developed with this configuration and preliminary results are included.

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The main aim of this paper is to design a hybrid force-position controller using fuzzy logic (FL) for the robotic arm of a 9 degrees of freedom (DOF) upper limb wearable exoskeleton rehabilitation robot. The robot is designed and built in our lab for assisting in the rehabilitation of patients post-stroke. The robotic arm of the rehabilitation robot is driven by pneumatic muscles (PM) and its dynamic performance is very complex. Fuzzy logic (FL) control techniques are applied to the robotic arm and the results show that FL controller shows better performances than that of the conventional PI controller in hybrid force-position control of the specified robotic arm of the rehabilitation robot.

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