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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The design of robots required to work in the close vicinity or physically interact with humans such as humanoids machines, rehabilitation or human performance augmentation systems should not follow the traditional design rule `stiffer is better’. Safety is a particularly vital concern in these systems and to maximize it a different design approach should be used. The role of compliance in improving specific suspects of the robotic system, including safety and energy efficiency, has been studied and validated in many works. This work presents the design and realization of a new variable compliance actuator for robots physically interacting with humans, e.g. prosthesis devices and exoskeleton augmentation systems. The actuator can independently control the equilibrium position and stiffness using two motors. The main novelty of the proposed variable stiffness actuator is that the stiffness regulation is achieved not through the pretension of the elastic elements which needs the stiffness tuning actuator to act against the forces generated by the springs but by mechanically adjusting the fixation of the spring elements. As a result the stiffness actuator does not need to act against the spring forces reducing the energy required for the stiffness adjustment to minimal.

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Knee ankle foot orthoses are prescribed to provide stability and maintain lower limb joints at their functional position. Current devices provide stability by locking joints permanently during the unsafe phase of a pathological gait (the stance phase). Though stability is obtained with such orthoses, gait patterns are unnatural and non-cosmetic. Other systems adapt more dynamically during gait, applying different strategies to recover or improve mobility. The system presented consist in a wearable set of sensors, actuators at knee and ankle joints, and a control and monitoring ambulatory unit, all integrated in a custom designed knee-ankle-foot robotic exoskeleton. A base unit allows wireless communication of the ambulatory unit, trough a Bluetooth link, with a PC software platform conceived for on-line and off-line data evaluation. Sensors adapted to the mechanical frame of the orthosis collect kinematics, such as angles at knee and ankle joints, and angular positions and accelerations at lower limb segments; kinetics, such as forces at the orthosis rods and fixation parts, and also foot contact information.

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Analysis of muscle activity by electrophysiological techniques is commonly used to analyze biomechanics. Although the simultaneous and intuitive understanding of both muscle activity and body motion is important in various fields, it is difficult to realize. This paper proposes a novel technique for visualizing physiological signals related to muscle activity by means of surface electromyography. We developed a wearable light-emitting interface that indicates lower-limb muscle activity or muscular tension on the surface of the body in real time by displaying the shape of the activated muscle. The developed interface allows users to perceive muscle activity in an intuitive manner by relating the level of the muscle activity to the brightness level of the glowing interface placed on the corresponding muscle. In order to verify the advantage of the proposed method, a cognitive experiment was conducted to evaluate the system performance. We also conducted an evaluation experiment using the developed interface in conjunction with an exoskeleton robot, in order to investigate the possible applications of the developed interface in the field of neuro-rehabilitation.

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In the effort to make robot-assisted upper limb passive movement training effective for neurologic injuries suffered from stroke and spinal cord injury (SCI), a new fuzzy adaptive closed-loop supervisory control method for passive joint movement training is proposed. Firstly, high-level supervisory controller for the desired passive range of motion (PROM) is designed based on the impaired limb’s joint motion recovery, and then low-level closed-loop position tracking controller is presented to drive the robot stably and smoothly to stretch the impaired limb to move along the predefined trajectory. The suggested strategy was applied to the four degrees of freedom (DOF) Whole Arm Manipulator (WAM) rehabilitation robot to evaluate its performance. Experimental results carried out on the 4-DOF WAM rehabilitation robot show the effectiveness and potentialities of the fuzzy adaptive passive movement control in clinical application.

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