Conventional robotic rehabilitation devices for upper extremity are bulky, heavy or lack the ability to provide joint level rehabilitation. Some designs address these issues by replacing rigid links of the exoskeletons with light weight cables. However these designs are controlled in position mode instead of force control which is desirable for rehabilitation. In this paper, a 5 degree-of-freedom cable-driven upper arm exoskeleton, with control of force, is proposed. In this design, attachment points of cables on the arm are adjustable. The attachment points are optimized to achieve large workspace to perform activities of daily living. Simulation results of force field control for training and rehabilitation of the arm are presented. Experiments have been performed on a dummy robotic arm in the upper arm exoskeleton.

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Background: The overall goal of this paper was to investigate approaches to controlling active participation in stroke patients during robot-assisted gait therapy. Although active physical participation during gait rehabilitation after stroke was shown to im-prove therapy outcome, some patients can behave passively during rehabilitation, not maximally benefiting from the gait training. Up to now, there has not been an effective method for forcing patient activity to the desired level that would most benefit stroke patients with a broad variety of cognitive and biomechanical impairments. Methods: Patient activity was quantified in two ways: by heart rate (HR), a physiological parameter that reflected physical effort during body weight supported treadmill training, and by a weighted sum of the interaction torques (WIT) between robot and patient, recorded from hip and knee joints of both legs. We recor-ded data in three experiments, each with five stroke patients, and controlled HR and WIT to a desired temporal profile. Depending on the patient’s cognitive capabilities, two different approaches were taken: either by allowing voluntary patient effort via visu-al instructions or by forcing the patient to vary physical effort by adapting the treadmill speed. Results: We successfully control-led patient activity quantified by WIT and by HR to a desired level. The setup was thereby individually adaptable to the specific cognitive and biomechanical needs of each patient. Conclusion: Based on the three successful approaches to controlling patient participation, we propose a metric which enables clinicians to select the best strategy for each patient, according to the pati-ent’s physical and cognitive capabilities. Our framework will enable therapists to challenge the patient to more activity by automa-tically controlling the patient effort to a desired level. We expect that the increase in activity will lead to improved rehabili-tation outcome.

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This paper introduces NEUROExos, an elbow powered exoskeleton for rehabilitation. The NEUROExos is provided with three novel characteristics which address the major problems arising in rehabilitation robotics. A double-shell link structure allows for a comfortable human-robot interaction, while a 4-DOF passive mechanism gives a perfect kinematic compatibility with the user. Moreover, NEUROExos is powered by a variable impedance antagonistic actuator, which provides the exoskeleton with a software-controllable passive compliance. We present the main characteristics of the exoskeleton, with a focus on the actuation and control of the platform. Additionally, results on a healthy subject show the relevance of this design during a prototypical rehabilitation task.

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This paper investigates the control algorithm of an exoskeleton for hand rehabilitation, which can realize the active, passive, and assisted rehabilitation motion. The active mode is accomplished with the force control algorithm during which the resistance is compensated in free space and the virtual interactive force is rendered to the finger in constraint space. The passive mode is realized by the position controller given the desired motion trajectory. The assisted mode is implemented in the customized positions by switching between the active and passive modes according to the predefined action procedure. The experiments are conducted to verify the proposed method, and the results show that the different rehabilitation motion are successfully accomplished and the maximum joint position error is less than 1.2 degree, which satisfies the requirement in hand rehabilitation application. The results demonstrate the validity of the proposed method.

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Most exoskeleton designs rely on structures and mechanical joints that do not guarantee the right match between the orthosis and the user. This paper proposes a virtual joint model based on three active degrees of freedom aimed to emulate a human joint. This joint is capable of performing a dynamic servo-adaptation in real-time to avoid misalignments and to provide a flexible adjustment to different users’ sizes in order to avoid undesirable interaction forces.

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