Reaching and Grasping Training based on Robotic Hybrid Assistance for Neurological Patients

Maria Bulgheroni, Enrico d'Amico, Ilaria De Vita, Emilia Ambrosini, Simona Ferrante, Thomas Schauer, Margit Gfoehler, Johannes Zajc, Michael Russold, Matthias Weber, Silvestro Micera, Karsten Krakow, Mauro Rossini, Giulio Gasperini, and Alessandra Pedrocchi


Robotics assistance, Neuromuscular electrical stimulation , Upper-limb rehabilitation, Embedded control system


This research tunes and validates advanced robot-based technologies to facilitate recovery of arm and hand function in stroke survivors. RETRAINER system is robotic hybrid assistance allowing the end-users to use their own arm and hand as much and as soon as possible after the stroke, to achieve the best outcomes in rehabilitation. Residual functionality is trained and improved. RETRAINER uses two sub-systems: S1 to train the arm movements and S2 to train the hand movements. S1 provides the end-user with an exoskeleton that does not completely take over the end-user's tasks and substitute the functionality of the body, but supports the end-user only whenever he/she really needs support. Arm movements is supported by the combined action of the passive exoskeleton described above for weight relief and Neuromuscular Electrical stimulation (NMES) delivered to subject-specific arm muscles in a controlled manner. S2 is a hand orthosis equipped with a novel wearable NMES system with multiple electrode arrays, which is a modular tool usable as a platform for grasp rehabilitation potentially improving the clinical applicability of NMES. Both the systems benefit from the use of smart interactive objects. A set of prototypes of the RETRAINER systems are being produced to allow a wide clinical testing of the effectiveness of robotic hybrid assistance in upper limb rehabilitation. High cooperation of technical and clinical experts since the early phases of design and development to the setup and running of the clinical trial is an added value of the implemented scientific approach.

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