PMC:2944670 / 57287-58918
Annnotations
{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/2944670","sourcedb":"PMC","sourceid":"2944670","source_url":"https://www.ncbi.nlm.nih.gov/pmc/2944670","text":"Rehabilitative interventions aimed at functional motor recovery in stroke patients are based mainly on active movement training such as constraint-induced therapy and/or passive mobilization (Liepert et al., 2000; Schaechter, 2004; Wolf et al., 2006). Recent clinical trials have provided new insights into the methods to assist motor recovery after stroke (Dobkin, 2008; Langhorne et al., 2009; Subramanian et al., 2010). A recurrent theme is that interventions emphasizing intense active repetitive task-oriented movements are of high value in this regard. To promote the effects of training and practice, biomedical engineers, neuroscientists, and clinicians have started an intense joint collaboration over the past 10 years. This technological approach holds a promise for enhancing traditional post-stroke recovery in different ways: exercise in virtual environments could provide feedback to aid skills learning (Jack et al., 2001; Holden et al., 2005; Merians et al., 2006); robotic assistive devices with sensory feedback for repetitive practice could provide therapy for a long periods of time, in a consistent and measurable manner (Takahashi et al., 2008; Volpe et al., 2009); FES of muscles might enable movements not otherwise possible during the practice of tasks such as reaching to grasp an object (Alon et al., 2007). These are only a part of the increasing technological developments which have been recently applied in sample of stroke patients and showed the feasibility in providing a clear incremental reduction of motor impairments offering, therefore the opportunity to build a better outcome for 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