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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Currently, wearers of full body exoskeletons are hindered in their ability to use their upper body as desired due to the rigid back parts used in these devices. In order to maximize their versatility the design and preliminary testing is shown of an exoskeletal spine mechanism, called “exo-spine”, that allows the wearer to move all degrees of freedom of his spine and shoulder girdle. Based on the primary forces to be supported during lifting, identified as gravity forces from loads lifted in front of the wearer, as well as functional degrees of freedom, which is a control strategy used by our central nervous system, this mechanism can be actuated using only one motor to provide the required support. Experiments indicate a substantial, although not problematic amount of friction as well as further requirements for the control of the assisting force. Besides improving exoskeletons its basic structure and design principles may be successfully applied to rehabilitation as well.

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Coupling the human upper limbs with robotic devices is gaining increasing attention in the last decade, due to the emerging applications in orthotics, prosthetics and rehabilitation devices. In the cases of every-day life tasks, force exertion and generally interaction with the environment is absolutely critical. Therefore, the decoding of the user’s force exertion intention is important for the robust control of orthotic robots (e.g. arm exoskeletons). In this paper, the human arm manipulability is analyzed and its effect on the recruitment of the musculo-skeletal system is explored. It was found that the recruitment and activation of muscles is strongly affected by arm manipulability. Based on this finding, a decoding method is built in order to estimate force exerted in the three-dimensional (3D) task space from surface ElectroMyoGraphic (EMG) signals, recorded from muscles of the arm. The method is using the manipulability information for the given force task. Experimental results were verified in various arm configurations with two subjects.

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