Fixed-Base Exoskeleton applications have increased rapidly in the last few years, evidently as part of promising rehabilitation robotic programs of the robotics worldwide community, where in particular Human-Robot-Interaction (HRI) plays an important role in its design and control because they are tightly coupled to human-limbs. Exoskeletons embrace HRI as well as technological and theoretical challenges towards real and effective rehabilitation. In this realm, some questions arise, to name a few, what is the relationship between the exchanged energy between human and exoskeleton? How can we assess rehabilitation factors under HRI philosophy? This paper attempts to establish answers to these questions, which can be embodied into rehabilitation HRI using a Light-Exoskeleton. A compliant haptic guidance scheme for human arm subject to minimum-jerk-trajectories criterion is proposed. Preliminary experimental results provide further insight of a haptic guidance scheme taking into account decisive factors into the HRI such as human pose, haptic guidance control, reaching and tracking tasks, the complexity of the virtual environment, and muscles activity.

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An exoskeleton has to be lightweight, compliant, yet powerful to fulfill the demanding task of walking. This imposes a great challenge for the actuator design. Electric motors, by far the most common actuator in robotic, orthotic, and prosthetic devices, cannot provide sufficiently high peak and average power and force/torque output, and they normally require high-ratio, heavy reducer to produce the speeds and high torques needed for human locomotion. Studies on the human muscle-tendon system have shown that muscles (including tendons and ligaments) function as a spring, and by storing energy and releasing it at a proper moment, locomotion becomes more energy efficient. Inspired by the muscle behavior, we propose a novel actuation strategy forexoskeleton design. In this paper, the collected gait data are analyzed to identify the spring property of the human muscle-tendon system. Theoretical optimization results show that adding parallel springs can reduce the peak torque by 66%, 53%, and 48% for hip flexion/extension (F/E), hip abduction/adduction (A/A), and ankle dorsi/plantar flexion (D/PF), respectively, and the rms power by 50%, 45%, and 61%, respectively. Adding a series spring (forming a Series Elastic Actuator, SEA) reduces the peak power by 79% for ankle D/PF, and by 60% for hip A/A. A SEA does not reduce the peak power demand at other joints. The optimization approach can be used for designing other wearable robots as well.

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This paper develops a novel system which includes an exoskeleton upper-limb robot and an inertia motion unit (IMU) measurement system based on mirror therapy concepts with assistive robotics. By integrating the IMU measurement system and the exoskeleton robot, we can execute measurement and control over larger range of motion (ROM) and also improve the safety and user-friendliness of the system. In this paper, two methods using IMU to measure various orientations of parts of the master-side’s upper-limb have been proposed, and then the posture trajectory of the disabled part of the slave’s side will be automatically generated. Conceivably, these two methods can create more complex trajectories than conventional approaches which design specific type of trajectories. Besides that, the accuracy and safety of orientation measurement are very important issues when robot-assisted exercises are conducted. To achieve this objective, we particularly develop a point-to-point control system consisting of two different types of position measurement components along with a PID controller, and both monitor each other to make the system more robust and to prevent the single point of failure problem while the system is working.

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An exoskeleton hand robotic training device is specially designed for persons after stroke to provide training on their impaired hand by using an exoskeleton robotic hand which is actively driven by their own muscle signals. It detects the stroke person’s intention using his/her surface electromyography (EMG) signals from the hemiplegic side and assists in hand opening or hand closing functional tasks. The robotic system is made up of an embedded controller and a robotic hand module which can be adjusted to fit for different finger length. Eight chronic stroke subjects had been recruited to evaluate the effects of this device. The preliminary results showed significant improvement in hand functions (ARAT) and upper limb functions (FMA) after 20 sessions of robot-assisted hand functions task training. With the use of this light and portable robotic device, stroke patients can now practice more easily for the opening and closing of their hands at their own will, and handle functional daily living tasks at ease. A video is included together with this paper to give a demonstration of the hand robotic system on chronic stroke subjects and it will be presented in the conference.

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Using the wavelet neural networks, an adaptive control system, with two wavelet neural networks as controller and dynamics model identifier respectively, is developed for lower extreme carrying exoskeleton robot. Because the wavelet neural networks have the ability to approximate nonlinear functions and good advantage of time-frequency localization properties, this system can identify nonlinear system dynamic characters more precisely, and can map more complex control strategies. Results show that this control system is more effective than those based on normal controller, where the exoskeleton tracking precision is high and the operator feels very little torque.

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