Abstract
During the past decade, there has been a continuous exploration of how virtual environments can be used to facilitate motor recovery and relearning after neurological impairment. There are two goals for using virtual environments: to improve patients’ rehabilitation outcomes beyond our current capabilities or to supplement labor-intensive and time consuming therapies with technology-based interventions. After over a decade of investigation, it seems appropriate to determine whether we are succeeding in meeting such goals.
Acknowledgments
This work was supported in part by NIH grant RO1 HD42161 and by the National Institute on Disability and Rehabilitation Research Rehabilitation Engineering Research Center (Grant # H133E050011).
References
1. Laver KE, George S, Thomas S, Deutsch, JE, Crotty M. Virtual reality for stroke rehabilitation Cochrane Database Syst Rev 2011;7:CD008349.10.1002/14651858.CD008349.pub2Search in Google Scholar PubMed
2. Saposnik G, Levin M. Virtual reality in stroke rehabilitation: a meta-analysis and implications for clinicians. Stroke 2011;42:1380–6.10.1161/STROKEAHA.110.605451Search in Google Scholar PubMed
3. Lang C, Macdonald J, Gnip C. Counting repetitions: an observational study of outpatient therapy for people with hemiparesis post-stroke. J Neurol Phys Ther 2007;3:3–11.10.1097/01.NPT.0000260568.31746.34Search in Google Scholar PubMed
4. Kleim JA, Jones TA. Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. J Speech Lang Hear Res 2008;51:225-39.Search in Google Scholar
5. Adamovich S, Merians A, Boian R, Tremaine M, Burdea G, Recce M, et al. A virtual reality based exercise system for hand rehabilitation post stroke. Presence 2005;14:161–74.10.1162/1054746053966996Search in Google Scholar
6. Housman SJ, Scott KM, Reinkensmeyer DJ. A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis. Neurorehabil Neural Repair 2009;23:505–14.10.1177/1545968308331148Search in Google Scholar PubMed
7. Krebs HI, Mernoff S, Fasoli SE, Hughes R, Stein J, Hogan N. A comparison of functional and impairment-based robotic training in severe to moderate chronic stroke: a pilot study. Neuro Rehabil 2008;23:81–7.10.3233/NRE-2008-23108Search in Google Scholar
8. Lum PS, Burgar CG, Shor PC. Evidence for improved muscle activation patterns after retraining of reaching movements with the MIME robotic system in subjects with post-stroke hemiparesis. IEEE Trans Neural Syst Rehabil Eng 2004;12:186–94.10.1109/TNSRE.2004.827225Search in Google Scholar PubMed
9. Merians A, Fluet GG, Qiu Q, Saleh S, Lafond I, Adamovich SV. Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis. J Neuroeng Rehabil 2011;8:27.10.1186/1743-0003-8-27Search in Google Scholar PubMed PubMed Central
10. Duncan PW, Sullivan KJ, Behrman AL, Azen SP, Wu SS, Nadeau SE, et al. Body-weight-supported treadmill rehabilitation after stroke. N Engl J Med 2011;364:2026–36.10.1056/NEJMoa1010790Search in Google Scholar PubMed PubMed Central
11. Dobkin B, Apple D, Barbeau H, Basso M, Behrman A, Deforge D, et al. Weight-supported treadmill vs over-ground training for walking after acute incomplete SCI. Neurology 2006;66: 484–93.10.1212/01.wnl.0000202600.72018.39Search in Google Scholar PubMed PubMed Central
12. Lo AC, Guarino P, Krebs HI, Volpe BT, Bever CT, Duncan PW, et al. Multicenter randomized trial of robot-assisted rehabilitation for chronic stroke: Neurorehabil Neural Repair 2009;23:775–83.10.1177/1545968309338195Search in Google Scholar
13. Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol 2006;19:84–90.10.1097/01.wco.0000200544.29915.ccSearch in Google Scholar
14. Plautz EJ, Milliken GW, Nudo RJ. Effects of repetitive motor training on movement representations in adult squirrel monkeys: role of use versus learning. Neurobiol Learn Mem 2000;74: 27–55.10.1006/nlme.1999.3934Search in Google Scholar
15. Remple MS, Bruneau RM, VandenBerg PM, Goertzen C, Kleim JA. Sensitivity of cortical movement representations to motor experience: evidence that skill learning but not strength training induces cortical reorganization. Behav Brain Res 2001;23: 133–41.10.1016/S0166-4328(01)00199-1Search in Google Scholar
16. Fluet GG, Merians AS, Qui Q, Lafond I, Saleh S, Ruano V, et al. Robots integrated with virtual reality simulations for customized motor training in a person with upper extremity hemiparesis: acase study. J Neurol Phys Ther 2012;36:79–86.10.1097/NPT.0b013e3182566f3fSearch in Google Scholar PubMed PubMed Central
17. Cameirao MS, Badia SB, Oller ED, Verschure PF. Neurorehabilitation using the virtual reality based rehabilitation gaming system: methodology, design, psychometrics, usability and validation. J Neuroeng Rehabil 2010;7:48.10.1186/1743-0003-7-48Search in Google Scholar PubMed PubMed Central
18. Jack D, Boian R, Merians AS, Tremaine M, Burdea GC, AdamovichSV, et al. Virtual reality-enhanced stroke rehabilitation. IEEE Trans Neural Syst Rehabil Eng 2001;9:308–18.10.1109/7333.948460Search in Google Scholar PubMed
19. Tunik E, Saleh S, Adamovich S. Visuomotor discordance during visually-guided hand movement in Virtual Reality modulates sensorimotor cortical activity in healthy and hemiparetic subjects. IEEE Trans Neural Syst Rehabil Eng 2013;21:198–202.10.1109/TNSRE.2013.2238250Search in Google Scholar PubMed PubMed Central
20. Bagce HF, Saleh S, Adamovich SV, Tunik E. Visuomotor discordance in virtual reality: effects on online motor control. Conf Proc IEEE Eng Med BiolSoc 2011;7262–65.10.1109/IEMBS.2011.6091835Search in Google Scholar PubMed PubMed Central
21. Patton JL, Stoykov ME, Kovic M, Mussa-Ivaldi FA. Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res 2006;168:368–83.10.1007/s00221-005-0097-8Search in Google Scholar PubMed
22. Patton JL, Wei YJ, Bajaj P, Scheidt RA. Visuomotor learning enhanced by augmenting instantaneous trajectory error feedback during reaching. PLoS ONE 2013;8:e46466.10.1371/journal.pone.0046466Search in Google Scholar PubMed PubMed Central
23. Qiu Q, Ramirez DA, Saleh S, Fluet GG, Parikh HD, Kelly D, et al. The New Jersey Institute of Technology Robot-Assisted Virtual Rehabilitation (NJIT-RAVR) system for children with cerebral palsy: a feasibility study. J Neuroeng Rehabil 2009;6:40.10.1186/1743-0003-6-40Search in Google Scholar PubMed PubMed Central
24. Fluet GG, Qiu Q, Kelly DF, Parikh HD, Ramirez D, Saleh S, et al. Intefacing a haptic robotic system with complex virtual environments to treat impaired upper extremity motor function in children with cerebral palsy. Dev Neurorehabil 2010;13:335–45.10.3109/17518423.2010.501362Search in Google Scholar PubMed PubMed Central
25. van Kordelaar J, van Wegen EE, Nijland RH, de Groot JH, Meskers CG, Harlaar J, et al. Assessing longitudinal change in coordination of the paretic upper limb using on-site 3-dimensional kinematic measurements. Phys Ther 2012;92:142–51.10.2522/ptj.20100341Search in Google Scholar PubMed
©2014 by De Gruyter
