The development of innovative exoskeletons for the upper limb requires a strong collaboration between robotics and neuroscience. The robotic system will be deeply coupled to the human user and the exoskeleton design should be based on the human model in terms of biomechanics, and control and learning strategies. This paper presents the preliminary results of the design process of the Neurobotics exoskeleton (NEUROexos). A bioinspired three joints-three links robotic arm is under development for implementing bioinspired control strategies and for obtaining a human-like robotic arm to be used for assessing active exoskeletons in fully safe conditions. In particular, this paper presents the shoulder joint-first link prototype, the selected actuation system, the actuator modelling and identification, and the experimental evaluation of the prototype capability to replicate the human shoulder kinematics during the execution of a catching task.

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Stroke forms one of the leading causes of death amongst adults in industrialized countries, and although survival rates are comparatively high in up to 1/3 of patients there is functional impairments (particularly in the upper limbs) that can persist even after rehabilitation training. Tasked based rehabilitation therapy (shaping) is a new approach that seems to offer good success compared to traditional methods, however, the technique requires very intensive and prolonged treatment. Robot mediated physiotherapy is the recent answer to the shortage of staff and the cost associated with this. In this paper a robotic approach to task based therapy is shown. The work focuses on how a robotic exoskeleton operating in a 3D volume can be used in conjunction with a Virtual Environment rehabilitation suite for training patients in relearning daily motor tasks. Salford RehabilitationExoskeleton (SRE) is used as an assistive device which helps individuals retrain in performing motor tasks by assisting them to complete therapy regimes. EMG recordings are used to show the capacity of the system to mediate the level of assistance provided from full assistance to zero aid.

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Evidence from biomechanics research suggests that tendon series elasticity allows muscle to act in an optimal range of its force–length and force–velocity curves to achieve work and power amplification. In this investigation we put forth a simple model to quantify the capacity of series elasticity to increase work and power output from an actuator. We show that an appropriate spring constant increases the energy that an actuator can deliver to a mass by a factor of 4. The series elasticity changes the actuator operating point along its force–velocity curve and therefore affects the actuator work output over a fixed stroke length. In addition, the model predicts that a series spring can store energy and deliver peak powers greater than the power limit of the source by a factor of 1.4. Preliminary experiments are performed to test model predictions. We find qualitative agreement between the model and experimental data, highlighting the importance of series elasticity for actuator work and power amplification across a fixed stroke length. We present several non-dimensional relations that can aid designers in the fabrication of robotic and prosthetic limbs optimized for work and power delivery.

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Biomechanical loading, in particular, viscous loading of the upper limb has been proposed in the literature as a means for suppressing pathologic tremor. It is expected that an improvement on manipulative function can be obtained by reducing the tremorous motion associated to some neurological disorders. This article presents two non-grounded control strategies to suppress tremor by means of a orthotic (wearable) exoskeleton. These two strategies are based on biomechanical loading and notch filtering of tremor via internal forces. Both controls strategies are evaluated and validated on the robotic exoskeleton called WOTAS (wearable orthosis for tremor assessment and suppression). At the end, results obtained in the pre-clinical trials and conclusions of this study are presented.

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The Berkeley lower extremity exoskeleton (BLEEX) is a load-carrying and energetically autonomous human exoskeleton that, in this first generation prototype, carries up to a 34 kg (75 Ib) payload for the pilot and allows the pilot to walk at up to 1.3 m/s (2.9 mph). This article focuses on the human-in-the-loop control scheme and the novel ring-based networked control architecture (ExoNET) that together enable BLEEX to support payload while safely moving in concert with the human pilot. The BLEEX sensitivity amplification control algorithm proposed here increases the closed loop system sensitivity to its wearer’s forces and torques without any measurement from the wearer (such as force, position, or electromyogram signal). The tradeoffs between not having sensors to measure human variables, the need for dynamic model accuracy, and robustness to parameter uncertainty are described. ExoNET provides the physical network on which the BLEEX control algorithm runs. The ExoNET control network guarantees strict determinism, optimized data transfer for small data sizes, and flexibility in configuration. Its features and application on BLEEX are described.

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