The objective of this study was to determine the utility of a passive gravity-balanced arm orthosis, the Wilmington roboticexoskeleton (WREX), for patients with neuromuscular diseases. The WREX, a four-degrees-of-freedom functional orthosis, is energized by rubber bands to eliminate gravity and is attached to the wheelchair. The development and clinical testing of WREX is described in this report. Seventeen patients (14 boys and 3 girls) with muscular disabilities participated in the study. Ages ranged from 4 to 20 years. Criteria for inclusion included a weakened arm, use of a wheelchair, the ability to grasp and release objects, and the ability to provide feedback on device use. Testing consisted of administering the Jebsen test of hand function without WREX and then testing again after approximately two weeks of wearing the WREX orthosis. The timed results of each task within the test then were compared. Specific tasks related to vertical movement required less time to perform with the WREX. A large number of subjects were able to perform the Jebsen tasks with the WREX, where they were unable to perform the task without the WREX. Patients can benefit from WREX because it increases their performance in daily living activities and makes many tasks possible. The range-of-motion in the patients’ arms increased considerably, while the time required to complete some of the Jebsen test tasks decreased. Most patients were very receptive to WREX, although a few were ambivalent.

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>We proposed a framework of using neural oscillators to control a robotic suit which learns to synchronize with the human user’s motion. The robotic suit is a lower limb exoskeleton consisting of four actuators which are fixed to the places where the human hip joints and knee joints are. Each actuator has a built-in harmonic drive gear which is equipped with a torque sensor fixed on the flex-spline. The torque sensor helps to measure the mutual joint torque, which will be generated by once there is any differences between human’s and suit’s movement. The neural oscillator connected to each joint controls each actuator through synchronizing the actuator’s desired joint angle with the feedback mutual joint torque. Proportional-integral-derivative (PID) control is then used to determine the real joint angle of each actuator. We have conducted experiments to show whether: 1) the synchronous movement of robotic suit is realized; 2) the synchronized movement has the application potential for walking assistance and rehabilitation. The results showed the potential of applying the synchronization based control to the robotic suit for walking assistance and rehabilitation purposes.

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A lot of research has been done in robot path generation, including automatic path planning and teaching/playback. Teleoperation is commonly used to control a robot from a remote site in an unknown environment. Korea Institute of Science and Technology (KIST) is developing a Humanoid robot, which has two arms (9 degrees of freedom for each), two hands (4 d.o.f. each), a waist (3 d.o.f.) and a neck (2 d.o.f.) An automatic path planner which takes advantage of redundancy is also developed, however, it requires huge computational power and time. For some tasks, which are very complex, or interacting with environments, the robot path can be generated very easily and accurately by human teaching, hence the automatic path planner is not required. Using sensors, human motion is analyzed and converted to robot joint angles. For tasks interacting with an unknown environment, teleoperation with force feedback is more useful. A simple exoskeleton-type master arm is designed based on kinematic analysis. For force reflection, pneumatic actuators are used. This device is integrated with KIST Humanoid robots. A force reflecting master hand is also developed. In addition to the master arm/hand, visual information is fed back to the human through HMD for higher interaction, and voice command interpreter/voice synthesis is integrated. Therefore a new method of human/robot integration is developed

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Motivation and voluntary drive of patients can be improved by applying biofeedback during robot-assisted rehabilitation trainings. Biofeedback systems were traditionally based on theoretical assumptions. In this paper, we present a novel approach to calculate biofeedback during robot-assisted gait training. Our method was based on empirical data that were obtained from healthy subjects when simulating distinctive degrees of walking performance during robot-assisted gait training. This empirical data-based biofeedback (EDBF) method was evaluated with 18 subjects without gait disorders. A higher correlation between the subjects’ walking performance and biofeedback values was found for the EDBF method compared to a theory-based biofeedback approach.

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One of the major outcomes of the EPSRC/British Aerospace supported project “Enabling Tactile Technology Environments”, was the Reactabot, a three degree of freedom force feedback device which provides tactual/kinaesthetic feedback to an operator via a surrogate object. Systems of this nature exhibit unwanted oscillatory behaviour and eventually instability if the virtual mass is reduced to too low a value, corresponding to raising the loop gain too high. The onset of this behaviour is found to be operator dependent. This paper studies the phenomenon in detail, modelling both the open loop system and human operator in the feedback path. It is shown that the variation between operators, allied with the unwanted but inevitable phase lags in the open loop system, cause the undesirable behaviour and suggestions are made to minimise their effect

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