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      Learning and transfer of complex motor skills in virtual reality: a perspective review

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          Abstract

          The development of more effective rehabilitative interventions requires a better understanding of how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design interventions to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for a target. While these tasks facilitate stringent hypothesis testing in laboratory settings, the results may not shed light on performance of more complex real-world skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms to evaluate learning and transfer of complex skills without sacrificing experimental control. Specifically, VEs use models of real-life tasks that afford controlled experimental manipulations to measure and guide behavior with a precision that exceeds the capabilities of physical environments. This paper reviews recent insights from VE paradigms on motor learning into two pressing challenges in rehabilitation research: 1) Which training strategies in VEs promote complex skill learning? and 2) How can transfer of learning from virtual to real environments be enhanced? Defining complex skills by having nested redundancies, we outline findings on the role of movement variability in complex skill acquisition and discuss how VEs can provide novel forms of guidance to enhance learning. We review the evidence for skill transfer from virtual to real environments in typically developing and neurologically-impaired populations with a view to understanding how differences in sensory-motor information may influence learning strategies. We provide actionable suggestions for practicing clinicians and outline broad areas where more research is required. Finally, we conclude that VEs present distinctive experimental platforms to understand complex skill learning that should enable transfer from therapeutic practice to the real world.

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          Principles derived from the study of simple skills do not generalize to complex skill learning.

          We review research related to the learning of complex motor skills with respect to principles developed on the basis of simple skill learning. Although some factors seem to have opposite effects on the learning of simple and of complex skills, other factors appear to be relevant mainly for the learning of more complex skills. We interpret these apparently contradictory findings as suggesting that situations with low processing demands benefit from practice conditions that increase the load and challenge the performer, whereas practice conditions that result in extremely high load should benefit from conditions that reduce the load to more manageable levels. The findings reviewed here call into question the generalizability of results from studies using simple laboratory tasks to the learning of complex motor skills. They also demonstrate the need to use more complex skills in motor-learning research in order to gain further insights into the learning process.
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            Virtual reality in stroke rehabilitation: a meta-analysis and implications for clinicians.

            Approximately two thirds of stroke survivors continue to experience motor deficits of the arm resulting in diminished quality of life. Conventional rehabilitation provides modest and sometimes delayed effects. Virtual reality (VR) technology is a novel adjunctive therapy that could be applied in neurorehabilitation. We performed a meta-analysis to determine the added benefit of VR technology on arm motor recovery after stroke. We searched Medline, EMBASE, and Cochrane literature from 1966 to July 2010 with the terms "stroke," "virtual reality," and "upper arm/extremity." We evaluated the effect of VR on motor function improvement after stroke. From the 35 studies identified, 12 met the inclusion/exclusion criteria totaling 195 participants. Among them, there were 5 randomized clinical trials and 7 observational studies with a pre-/postintervention design. Interventions were delivered within 4 to 6 weeks in 9 of the studies and within 2 to 3 weeks in the remaining 3. Eleven of 12 studies showed a significant benefit toward VR for the selected outcomes. In the pooled analysis of all 5 randomized controlled trials, the effect of VR on motor impairment (Fugl-Meyer) was OR=4.89 (95% CI, 1.31 to 18.3). No significant difference was observed for Box and Block Test or motor function. Among observational studies, there was a 14.7% (95% CI, 8.7%-23.6%) improvement in motor impairment and a 20.1% (95% CI, 11.0%-33.8%) improvement in motor function after VR. VR and video game applications are novel and potentially useful technologies that can be combined with conventional rehabilitation for upper arm improvement after stroke.
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              Virtual Reality Therapy for Adults Post-Stroke: A Systematic Review and Meta-Analysis Exploring Virtual Environments and Commercial Games in Therapy

              Background The objective of this analysis was to systematically review the evidence for virtual reality (VR) therapy in an adult post-stroke population in both custom built virtual environments (VE) and commercially available gaming systems (CG). Methods MEDLINE, CINAHL, EMBASE, ERIC, PSYCInfo, DARE, PEDro, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews were systematically searched from the earliest available date until April 4, 2013. Controlled trials that compared VR to conventional therapy were included. Population criteria included adults (>18) post-stroke, excluding children, cerebral palsy, and other neurological disorders. Included studies were reported in English. Quality of studies was assessed with the Physiotherapy Evidence Database Scale (PEDro). Results Twenty-six studies met the inclusion criteria. For body function outcomes, there was a significant benefit of VR therapy compared to conventional therapy controls, G = 0.48, 95% CI = [0.27, 0.70], and no significant difference between VE and CG interventions (P = 0.38). For activity outcomes, there was a significant benefit of VR therapy, G = 0.58, 95% CI = [0.32, 0.85], and no significant difference between VE and CG interventions (P = 0.66). For participation outcomes, the overall effect size was G = 0.56, 95% CI = [0.02, 1.10]. All participation outcomes came from VE studies. Discussion VR rehabilitation moderately improves outcomes compared to conventional therapy in adults post-stroke. Current CG interventions have been too few and too small to assess potential benefits of CG. Future research in this area should aim to clearly define conventional therapy, report on participation measures, consider motivational components of therapy, and investigate commercially available systems in larger RCTs. Trial Registration Prospero CRD42013004338
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                Author and article information

                Contributors
                (617) 373-5198 , d.levac@northeastern.edu
                609 513 2229 , mehuber@mit.edu
                617-373-5093 , d.sternad@northeastern.edu
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                18 October 2019
                18 October 2019
                2019
                : 16
                : 121
                Affiliations
                [1 ]ISNI 0000 0001 2173 3359, GRID grid.261112.7, Department of Physical Therapy, Movement and Rehabilitation Sciences, , Northeastern University, ; 407c Robinson Hall, 360 Huntington Ave, Boston, MA 02115 USA
                [2 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Department of Mechanical Engineering, , Massachusetts Institute of Technology, ; 77 Massachusetts Ave, Bldg 3, Rm 143, Cambridge, MA 02139 USA
                [3 ]ISNI 0000 0001 2173 3359, GRID grid.261112.7, Biology, Electrical and Computer Engineering, and Physics, , Northeastern University, ; 503 Richards Hall, 360 Huntington Avenue, Boston, MA 02118 USA
                Author information
                http://orcid.org/0000-0001-7356-9335
                Article
                587
                10.1186/s12984-019-0587-8
                6798491
                31627755
                11be9d4f-946c-42be-80fd-a8da69b59f63
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 October 2018
                : 5 September 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100009633, Eunice Kennedy Shriver National Institute of Child Health and Human Development;
                Award ID: K01HD093838
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R01-HD087089
                Award ID: R01-HD081346
                Award ID: R21-HD089731
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: NSF-EAGER-1548514
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100001680, Charles H. Hood Foundation;
                Award ID: N/A
                Categories
                Review
                Custom metadata
                © The Author(s) 2019

                Neurosciences
                sensorimotor control,motor learning,transfer,complex skills,virtual reality,virtual environments,rehabilitation,variability,redundancy

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