Surface electromyogram (SEMG) signal driven exoskeleton system is now gaining more research interests due to the promise of offering a faster response haptic system than the traditional position or force driven exoskeleton system. However, the technology to control and drive the exoskeleton system using myosignal is still not well established. The major problem of implementing the SEMG signal into the system comes from its naturally random and inconsistence properties. This research work investigates the optimal use of SEMG signal acquisition to drive an exoskeleton system. Two major criteria are identified as the essential conditions for the acquired SEMG signal as being suitable for driving an exoskeleton system robustly. Firstly, the magnitudes of measured SEMG signals have to show significant positive changes with increasing of external load. Secondly, the patterns of SEMG signal are required to be consistent for a particular muscle action. The former part of this paper shows some essential procedures for satisfying the first criteria along with the different configurations of the experimental set-up that were performed. The results were compared so as to determine the best settings for the SEMG signal recording in order to obtain the consistent muscle activity measuring in Biceps Brachii and Brachioradialis muscles.

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This paper introduces an exoskeleton assistive hand that supports human hand and wrist activities by using user’s bioelectric potential to control the exoskeleton movement. The exoskeleton has three active joints for an index finger, three active joints for combination of a middle finger, a ring finger and a little finger and two active joints for a thumb. It also has two passive joints between the index finger part and the combined part of the three fingers. Our proposed poly-articular tendon drive mechanism simulates a mechanical compliance of a human finger so that the exoskeleton could realize comfortable and stable grasping. This paper proposes a new mechanism «dual sensing system» and a new control algorithm «bioelectric potential-based switching control» so that the exoskeleton could synchronize wearer’s hand activities without any force sensor. A tendon-driven mechanism and a dual sensing system enable wearer’s fingers to move freely when they does need power assist but precise position control or force control. A bioelectric potential-based switching control enables the exoskeleton to augment their grasping force only when wearer’s fingers generate a relatively large grasping force. A five-parallel-link mechanism is used to assist wrist activities of a wearer. Through experiments it is confirmed that the exoskeleton does not disturb a wear’s pinch of a small object and that it augments grasping force for a heavy work.

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Recent technological advances made necessary the use of the robots in various types of applications. Currently, the traditional robot-like scenarios dedicated to industrial applications with repetitive tasks, were replaced by applications which require human interaction. The main field of such applications concerns the rehabilitation and aid of elderly persons. In this study, we present a state-of-the-art of the main research advances in lower limbs actuated orthosis/wearable robots in the literature. This will include a review on researches covering full limb exoskeletons, lower limb exoskeletons and particularly the knee joint orthosis. Rehabilitation using treadmill based device and use of Functional Electrical Stimulation (FES) are also investigated. We discuss finally the challenges not yet solved such as issues related to portability, energy consumption, social constraints and high costs of these devices.

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The aim of this study is to assess the feasibility of an approach for generating velocity-dependent trajectories to train neurologically injured patients. The reference trajectories are constructed based on the gait patterns of subjects walking on a treadmill. By extracting key events (parameters) from these trajectories, the velocity dependency of the parameters is determined by regression analysis. Then, splines are fitted through these points to obtain gait patterns (position, velocity and acceleration) for specific walking velocities. Considering the severely injured patients, a feedforward controller is used in addition to the impedance controller. The approach is implemented on the LOPES gait rehabilitation robot and evaluated on healthy subjects. Results indicate that the subjects can walk naturally in the robot with the constructed reference trajectories. Further improvements to the technical design and additional testing of healthy and impaired subjects are required to show whether this approach can be transferred to clinical domain.

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For gait rehabilitation robots, an important question is how to ensure stable gait, while avoiding any interaction forces between robot and human in case the patient walks correctly. To achieve this, the definition of ldquocorrectrdquo gait needs to adapted both to the individual patient and to the situation. Recently, we proposed a method for online trajectory generation that can be applied for hemiparetic subjects. Desired states for one (disabled) leg are generated online based on the movements of the other (sound) leg. An instantaneous mapping between legs is performed by exploiting physiological interjoint couplings. This way, the patient generates the reference motion for the affected leg autonomously. The approach, called Complementary Limb Motion Estimation (CLME), is implemented on the LOPES gait rehabilitation robot and evaluated with healthy subjects in two different experiments. In a previously described study, subjects walk only with one leg, while the robot’s other leg acts as a fake prosthesis, to simulate complete loss of function in one leg. This study showed that CLME ensures stable gait. In a second study, to be presented in this paper, healthy subjects walk with both their own legs to assess the interference with self-determined walking. Evaluation criteria are: Power delivered to the joints by the robot, electromyography (EMG) distortions, and kinematic distortions, all compared to zero torque control, which is the baseline of minimum achievable interference. Results indicate that interference of the robot is lower with CLME than with a fixed reference trajectory, mainly in terms of lowered exchanged power and less alteration of EMG. This implies that subjects can walk more naturally with CLME, and they are assisted less by the robot when it is not needed. Future studies with patients are yet to show whether these properties of CLME transfer to the clinical domain.

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