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Analysis of the Interlimb similarity of motor patterns for improving stroke assessment and neurorehabilitation

Stroke is the leading cause of adult disability, with upper limb hemiparesis being one of the most common consequences. Regaining voluntary arm movement is one of the major goals of rehabilitation. However, even with intensive rehabilitation, approximately 30% of patients remain permanently disabled and only 5 to 20% of them recover full independence. Hence, there is an increasing interest in incorporating the latest advances in neuroscience, medicine and engineering to improve the efficacy of conventional therapies. 
In the last years, a variety of promising targets have been identified to improve rehabilitation. However, there is no consensus on which measure should be applied as a gold standard to study functional recovery. This fact dramatically hinders the development of new interventions since it turns difficult to compare different clinical trials and draw consistent conclusions about therapeutic efficiency. In addition, available scales are subjective, qualitative and often lead to incongruent outcomes. Indeed, there is increasing suspicion that the lack of optimal assessment measures hampers the detection of benefits of new therapies. Moreover, existing scales totally ignore the neuromuscular state of the patient masking the ongoing recovery processes. In consequence, making appropriate clinical decisions in such environment is almost impossible. 
In light of all these facts, the need for new objective biomarkers to develop effective therapies is undeniable. To give response to these demands we have organized this thesis into two main branches. On the one hand, we have developed an innovative physiological scale that reveals the neuromuscular state of the patient and is able to discriminate between motor impairment levels. The innovation here resides in the concept of interlimb similarity (ILS). Based on the latest findings about the modular organization of the motor system and taking into account that stroke provokes unilateral motor damage, we propose comparing the control structure of the unaffected arm with the control structure of the paretic arm to quantify motor impairment. 
We have defined the control structure as the set of muscle synergies and activation coefficients needed to complete a task. The advantage of this approach is not only its capacity to provide neuromuscular information about the patient, but also that the ILS is personalized to each patient and can purposely guide rehabilitation based on the patient?s own physiological patterns. This supposes a huge advance taking into account the heterogeneity of stroke pathogenesis. 
On other hand, we have characterized the therapeutic potential of Visual Feedback (VF) as a tool to purposely induce neuroplastic changes. We have chosen VF among the various interventions proven to improve motor performance, because VF is a cheap strategy that can be implemented in almost any rehabilitation center. We demonstrate that VF is able to modulate the human control structure. In healthy subjects, it seems that VF makes accessible the refined dominant motor programs for the nondominant hemisphere giving rise to an increased interlimb similarity of the control structure. Interestingly, in stroke patients VF is able to manipulate the ILS of upper-limb kinematics in favor of finer motor control but a single training session seems not to be enough to fix those changes in the neuromuscular system of a damaged brain. 
Overall, these findings offer a new promising framework to develop and assess an effective intervention to guide the restoration of the original neuromuscular patterns and avoid unwanted maladaptive neuroplasticity. In conclusion, this thesis seeks moving forward in the understanding of human motor recovery processes and their relationship with neuroplasticity. In this sense, it provides important advances in the design of a new biomarker of motor impairment and tests the power of VF to modulate the neuromuscular control of patients with stroke.