In this paper, a real-time upper limb’s motion tracking exoskeleton device is proposed and developed, which can be used in active rehabilitation of upper limb for stroke. This device is portable and wearable and is potential to be used in the passive and active training for stroke patients. Passive training has been finished in previous work and in this paper, the preliminary work for active rehabilitation is presented, which is realization of the real-time upper limb’s motion tracking. We use an adaptive weighted average filtering and double close-loop control to realize real-time and stable tracking performance. Experiments have been conducted to prove that it is suitable for active rehabilitation.

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This contribution discusses the advanced technologies integration: the PERCRO light-exoskeleton and the PERCRO data-glove wherein the main pursuit is the enhancement of the human grasping skills inside virtual environments. The mastering of motor human skills for taking up, lifting or manipulating objects during grasping tasks, could be effectively enhanced thanks to the inclusion of an arm exoskeleton which provides arm haptic-guidance-positioning (HGPo) into spatial coordinates and the data-glove for hand dexterity practicing. This paper takes into account a synergetic fusion of theoretical concepts and practical developments, pointing out the feasibility of having robust and accurate hand/arm haptic-robotic guidance positioning within virtual reality environments. Notice that those applications demand high precision, robustness, repeatability and hand/arm dexterity; such a mentioned properties are covered by the proposed system.

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A deformable non-uniform rational B-spline (NURBS) based volume is programmed for the Iowa State University (ISU) force-reflecting exoskeleton haptic device. A direct free-form deformation (DFFD) technique is applied for realistic manipulation. In order to implement real-time deformation, a nodal mapping technique is used to connect points on the virtual object with the NURBS volume. This geometric modeling technique is ideally incorporated with the force-reflecting haptic device as a virtual interface. The results presented in this paper introduce details for the complete set-up for a realistic virtual clay modeling task with force feedback. The ISU force-reflecting exoskeleton, coupled with a supporting PUMA 560 manipulator and the virtual clay model are integrated with the WorldToolKit (WTK) graphics display, and the results show that the force feedback from the realistic physically-based virtual environment can greatly enhance the sense of immersion.

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Human hand is easy to be injured. As physical rehabilitation therapy after a hand operation always takes a long time, the curative effect gets worse and the social and financial hardship with physical deterioration can be caused. A CPM machine is a mechanism based on the rehabilitation theory of continuous passive motion (CPM). To improve rehabilitation results and validate the CPM theory we have developed a portable exoskeleton based CPM machine. The device can be easily attached and also be adjusted to fit different hand sizes. And during the finger’s flexion and extension motion the machine can always exert perpendicular forces on the finger phalanges. It can achieve the precise control of scope, force and speed of the moving fingers. Finally based on its mechanical structure, a kinematic validation and simulation including kinematic simulation and dynamic simulation have been carried out.

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This paper is focused on designing of fuzzy based gains tuning of proportional-derivative (FTPD) controller for joints positions control of the Asian Institute of Technology’s leg exoskeleton-I (ALEX-I). The main objective of this research is to obtain the desired gait motion of the whole system. The gait data from simulation is used as the input (set point) of ALEX-I, this data is simulated based on body CM balancing criteria. Fuzzy logic controller applies five membership functions of error and rate of error, four KP and three KD singletons output gains are adjusted according with the defined fuzzy rules. The COGS defuzzification output is sent to ARM7 controllers which control all the system joints. The performance of FTPD controller is then compared with the conventional PD controller. The results show superior performance of FTPD in smaller position error, less percentage of power consumption and less oscillation of gait motion on ALEX-I.

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