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Neurotechnology is the application of scientific knowledge to the practical purpose of understanding, interacting and/or repairing the brain or, in a broader sense, the nervous system. The development of novel approaches to decode functional information from the brain, to enhance specific properties of neural tissue and to restore motor output in real end-users is a fundamental challenge to translate these novel solutions into clinical practice. In this Thesis, I introduce i) a novel imaging method to characterize movement-related electroencephalographic (EEG) potentials; ii) a brain stimulation strategy to improve brain-computer interface (BCI) control; iii) and a therapy for motor recovery involving a neuroprosthesis. Overall, results show i) that stable EEG topographies present a subject-independent organization that can be used to robustly decode actual or attempted movements in sub-acute stroke patients and healthy controls, with minimal a-priori information; ii) that transcranial direct-current stimulation (tDCS) enhances the modulability of sensorimotor rhythms used for brain-computer interaction in chronic Spinal Cord Injured (SCI) individuals and healthy controls; iii) that neuromuscular electrical stimulation (NMES) controlled via closed-loop neural activity induces significantly stronger upper limb functional recovery in chronic stroke patients than sham NMES therapy, and that these changes are clinically relevant. These results have or might have important implications in i) disease diagnostics and monitoring through EEG; ii) assistive technology and reduction of permanent disability following SCI; iii) rehabilitation and recovery of upper limb function following a stroke, also after several years of complete paralysis. Briefly, this Thesis provides the conceptual framework, scientific rationale, technical details and clinical evidence supporting translational Neurotechnology that improves, optimizes and disrupts current medical practice in monitoring, substituting and recovering lost upper limb function. |
