Healthy individuals modulate muscle activation patterns according to their intended movement and external environment. Persons with neurological disorders (e.g., stroke and spinal cord injury), however, have problems in movement control due primarily to their inability to modulate their muscle activation pattern in an appropriate manner. A functionality test at the level of individual muscles that investigates the activity of a muscle of interest on various motor tasks may enable muscle-level force grading. To date there is no extant work that focuses on the application of exoskeleton robots to induce specific muscle activation in a systematic manner. This paper proposes a new method, named “individual muscle-force control” using a wearable robot (an exoskeletonrobot, or a power-assisting device) to obtain a wider variety of muscle activity data than standard motor tasks, e.g., pushing a handle by hand. A computational algorithm systematically computes control commands to a wearable robot so that a desired muscle activation pattern for target muscle forces is induced. It also computes an adequate amount and direction of a force that a subject needs to exert against a handle by his/her hand. This individual muscle control method enables users (e.g., therapists) to efficiently conduct neuromuscular function tests on target muscles by arbitrarily inducing muscle activation patterns. This paper presents a basic concept, mathematical formulation, and solution of the individual muscle-force control and its implementation to a muscle control system with an exoskeleton-type robot for upper extremity. Simulation and experimental results in healthy individuals justify the use of an exoskeleton robot for future muscle function testing in terms of the variety of muscle activity data.

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This paper describes a robotic-arm exoskeleton that uses a parallel mechanism inspired by the human forearm to allow naturalistic shoulder movements. The mechanism can produce large forces through a substantial portion of the range of motion (RoM) of the human arm while remaining lightweight. This paper describes the optimization of the exoskeleton’s torque capabilities by the modification of the key geometric design parameters.

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Background: To improve design of robotic lower limb exoskeletons for gait rehabilitation, it is critical to identify neural mecha-nisms that govern locomotor adaptation to robotic assistance. Previously, we demonstrated soleus muscle recruitment decreased by ~35% when walking with a pneumatically-powered ankle exoskeleton providing plantar flexor torque under soleus proportional myoelec-tric control. Since a substantial portion of soleus activation during walking results from the stretch reflex, increased reflex in-hibition is one potential mechanism for reducing soleus recruitment when walking with exoskeleton assistance. This is clinically re-levant because many neurologically impaired populations have hyperactive stretch reflexes and training to reduce the reflexes could lead to substantial improvements in their motor ability. The purpose of this study was to quantify soleus Hoffmann (H-) reflex res-ponses during powered versus unpowered walking. Methods: We tested soleus H-reflex responses in neurologically intact subjects (n=8) that had trained walking with the soleus controlled robotic ankle exoskeleton. Soleus H-reflex was tested at the mid and late stance while subjects walked with the exoskeleton on the treadmill at 1.25 m/s, first without power (first unpowered), then with power (powered), and finally without power again (second unpowered). We also collected joint kinematics and electromyography. Re-sults: When the robotic plantar flexor torque was provided, subjects walked with lower soleus electromyographic (EMG) activation (27-48%) and had concomitant reductions in H-reflex amplitude (12-24%) compared to the first unpowered condition. The H-reflex am-plitude in proportion to the background soleus EMG during powered walking was not significantly different from the two unpowered conditions. Conclusion: These findings suggest that the nervous system does not inhibit the soleus H-reflex in response to short-term adaption to exoskeleton assistance. Future studies should determine if the findings also apply to longterm adaption to the exo-skeleton.

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Background: Stair climbing up and down is an essential part of everyday’s mobility. To enable wheelchair-dependent patients the repetitive practice of this task, a novel gait robot, G-EO-Systems (EO, Lat: I walk), based on the end-effector principle, has been designed. The trajectories of the foot plates are freely programmable enabling not only the practice of simulated floor wal-king but also stair climbing up and down. The article intended to compare lower limb muscle activation patterns of hemiparetic sub-jects during real floor walking and stairs climbing up, and during the corresponding simulated conditions on the machine, and se-condly to demonstrate gait improvement on single case after training on the machine. Methods: The muscle activation pattern of se-ven lower limb muscles of six hemiparetic patients during free and simulated walking on the floor and stair climbing was measured via dynamic electromyography. A non-ambulatory, sub-acute stroke patient additionally trained on the G-EO-Systems every workday for five weeks. Results: The muscle activation patterns were comparable during the real and simulated conditions, both on the floor and during stair climbing up. Minor differences, concerning the real and simulated floor walking conditions, were a delayed (prolonged) onset (duration) of the thigh muscle activation on the machine across all subjects. Concerning stair climbing conditions, the shank muscle activation was more phasic and timely correct in selected patients on the device. The severely affected subject regained wal-king and stair climbing ability. Conclusions: The G-EO-Systems is an interesting new option in gait rehabilitation after stroke. The lower limb muscle activation patterns were comparable, a training thus feasible, and the positive case report warrants further clinical studies.

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Ce projet s’inscrit dans l’effort développé par l’Agence Spatiale Européenne (ESA) pour robotiser les activités extravéhiculaires à bord de la Station Spatiale Internationale et lors des futures missions d’exploration planétaire. Un aspect important de ces projets concerne le retour de force et la capacité, pour la personne qui commande les mouvements du robot, à ressentir les efforts qui lui sont appliqués. Le but est d’améliorer la qualité et l’immersion de la téléopération. L’objectif de cette thèse est la conception d’une interface haptique de type exosquelette pour le bras, pour ces missions de téléopération à retour de force. Ce système doit permettre une commande intuitive du robot téléopéré tout en reproduisant le plus fidèlement possible les efforts. Les chapitres 2 et 3 présentent les études réalisées sur un banc de test à 1 degré de liberté, destinées à comprendre le contrôle haptique ainsi qu’à évaluer différentes technologies d’actionnements et de capteurs. Les principales méthodes de contrôle sont décrites théoriquement et comparées en pratique sur le banc de test. Les chapitres 4 et 5 décrivent le développement de l’exosquelette SAM destiné aux futures applications de téléopération spatiale. La conception cinématique, le choix des actionneurs et des capteurs sont décrits. Différentes méthodes de contrôle sont également comparées avec des expériences de réalité virtuelle (sans robot esclave) et de téléopération. Pour finir, le chapitre 6 présente le projet EXOSTATION, un démonstrateur de téléopération haptique spatiale, dans lequel SAM est utilisé comme interface maître.

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