This paper presents a human—machine interface to control exoskeletons that utilizes electrical signals from the muscles of the operator as the main means of information transportation. These signals are recorded with electrodes attached to the skin on top of selected muscles and reflect the activation of the observed muscle. They are evaluated by a sophisticated but simplified biomechanical model of the human body to derive the desired action of the operator. A support action is computed in accordance to the desired action and is executed by the exoskeleton. The biomechanical model fuses results from different biomechanical and biomedical research groups and performs a sensible simplification considering the intended application. Some of the model parameters reflect properties of the individual human operator and his or her current body state. A calibration algorithm for these parameters is presented that relies exclusively on sensors mounted on the exoskeleton. An exoskeleton for knee joint support was designed and constructed to verify the model and to investigate the interaction between operator and machine in experiments with force support during everyday movements.

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This paper describes the design and human machine interface of an Active Leg EXoskeleton (ALEX) for gait rehabilitation of patients with walking disabilities. The paper proposes force-field controller which can apply suitable forces on the leg to help it move on a desired trajectory. The interaction forces between the subject and the orthosis are designed to be ‘assist-as-needed’ for safe and effective gait training. Simulations and experimental results with the force-field controller are presented. Experiments have been performed with healthy subjects walking on a treadmill. It was shown that a healthy subject could be retrained in about 45 minutes with ALEX to walk on a treadmill with a significantly altered gait. In the coming months, this powered orthosis will be used for gait training of stroke patients.

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Most mobile exoskeletons use DC motors as actuators and batteries as power sources. While DC motor consumes a lot of power and limits the working time of the exoskeleton, it produces large impedance that would cause discomfort and danger to people. Magnetorheological (MR) fluid is a smart fluid that can change its rheological behavior under applied magnetic field. Devices using MR fluids have the benefits of high torque, good controllability, low power requirement, and safety. In this research, we develop a new MR actuator for leg exoskeleton. The MR actuator consists of a DC motor and an MR brake/clutch. When active torque is desired, the DC motor works and the MR actuator functions as a clutch to transfer the torque generated by the motor to the leg; when passive torque is desired, the DC motor is turned off and the MR actuator functions as a brake to provide controllable passive torque. The results show that the adaptive control can track the needed torque/power of the knee joint very well, even under the variation of parameters.

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A modular approach is proposed for controlling a robotic arm exoskeleton used for shoulder rehabilitation. The joints are partitioned into anthropomorphic sets based on the exercise protocol which are then commanded using separate control modules. The controllers run concurrently and can operate in either impedance or admittance mode. The approach is applied to the MGAexoskeleton, and some preliminary experimental results are given for both iso-lateral and functional training exercises.

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Finger impairment following stroke results in significant deficit in hand manipulation and the performance of everyday tasks. Recent advances in rehabilitation robotics have shown improvement in efficacy of rehabilitation. Current devices, however, lack the capacity to accurately interface with the human finger at levels of velocity and torque comparable to the performance of everyday hand manipulation tasks. To fill this need, we have developed the Actuated Finger Exoskeleton (AFX), a three degree-of-freedom robotic exoskeleton for the index finger. This paper outlines the implementation and initial kinematic analysis of the AFX.

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