Skip to main content

Virtual Reality for Sensorimotor Rehabilitation Post Stroke: Design Principles and Evidence

  • Chapter
  • First Online:
Neurorehabilitation Technology

Abstract

In the recent years, the use of virtual reality (VR) to enhance motor skills of persons with activity and participation restriction due to disease or injury has been become an important area of research. In this chapter, we describe the design of such VR systems and their underlying principles, such as experience-dependent neuroplasticity and motor learning. Further, psychological constructs related to motivation including salience, goal setting, and rewards are commonly utilized in VR to optimize motivation during rehabilitation activities. Hence, virtually simulated activities are considered to be ideal for (1) the delivery of specific feedback, (2) the ability to perform large volumes of training, and (3) the presentation of precisely calibrated difficulty levels, which maintain a high level of challenge throughout long training sessions. These underlying principles are contrasted with a growing body of research comparing the efficacy of VR with traditionally presented rehabilitation activities in persons with stroke that demonstrate comparable or better outcomes for VR. In addition, a small body of literature has utilized direct assays of neuroplasticity to evaluate the effects of virtual rehabilitation interventions in persons with stroke. Promising developments and findings also arise from the use of off-the-shelf video game systems for virtual rehabilitation purposes and the integration of VR with robots and brain-computer interfaces. Several challenges limiting the translation of virtual rehabilitation into routine rehabilitation practice need to be addressed but the field continues to hold promise to answer key issues faced by modern healthcare.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Burdea GC, Coiffet P. Virtual reality technology. Presence. 2003;12(6):663–4.

    Article  Google Scholar 

  2. Wilson PN, Foreman N, Stanton D. Virtual reality, disability and rehabilitation. Disabil Rehabil. 1997;19(6):213–20.

    Article  CAS  PubMed  Google Scholar 

  3. Adamovich SV, Fluet GG, Tunik E, Merians AS. Sensorimotor training in virtual reality: a review. Neurorehabilitation. 2009;25(1):29–44.

    PubMed  PubMed Central  Google Scholar 

  4. Slater M, Wilbur S. A framework for immersive virtual environments (FIVE): speculations on the role of presence in virtual environments. Presence. 1997;6(6):603–16.

    Article  Google Scholar 

  5. Lee KM. Presence, explicated. Commun Theory. 2004;14(1):27–50.

    Article  Google Scholar 

  6. Riva G. Is presence a technology issue? Some insights from cognitive sciences. Virtual Reality. 2009;13(3):159–69.

    Article  Google Scholar 

  7. Baños RM, Botella C, Alcañiz M, Liaño V, Guerrero B, Rey B. Immersion and emotion: their impact on the sense of presence. Cyberpsychol Behav. 2004;7(6):734–41.

    Article  PubMed  Google Scholar 

  8. Llorens R, Noe E, Naranjo V, Borrego A, Latorre J, Alcaniz M. Tracking systems for virtual rehabilitation: objective performance vs. subjective experience. A practical scenario. Sensors. 2015;15(3):6586–606.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Stanney KM, Mourant RR, Kennedy RS. Human factors issues in virtual environments: a review of the literature. Presence. 1998;7(4):327–51.

    Article  Google Scholar 

  10. Arzy S, Overney LS, Landis T, Blanke O. Neural mechanisms of embodiment: asomatognosia due to premotor cortex damage. Arch Neurol. 2006;63(7):1022–5.

    Article  PubMed  Google Scholar 

  11. Legrand D. The bodily self: the sensorimotor roots of pre-reflective self-consciousness. Phenom Cogn Sci. 2006;5(1):89–118.

    Article  Google Scholar 

  12. Berlucchi G, Aglioti S. The body in the brain: neural bases of corporeal awareness. Trends Neurosci. 1997;20(12):560–4.

    Article  CAS  PubMed  Google Scholar 

  13. Schultze U. Embodiment and presence in virtual worlds: a review. J Inf Technol. 2010;25(4):434–49.

    Article  Google Scholar 

  14. Longo MR, Schüür F, Kammers MPM, Tsakiris M, Haggard P. What is embodiment? A psychometric approach. Cognition. 2008;107(3):978–98.

    Article  PubMed  Google Scholar 

  15. Tsakiris M. My body in the brain: a neurocognitive model of body-ownership. Neuropsychologia. 2010;48(3):703–12.

    Article  PubMed  Google Scholar 

  16. Botvinick M, Cohen J. Rubber hands /‘feel/’ touch that eyes see. Nature. 1998;391(6669):756.

    Article  CAS  PubMed  Google Scholar 

  17. Petkova VI, Ehrsson HH. If I were you: perceptual illusion of body swapping. PLoS ONE. 2008;3(12), e3832.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Petkova VI, Khoshnevis M, Ehrsson HH. The perspective matters! Multisensory integration in ego-centric reference frames determines full body ownership. Front Psychol. 2011;2:35.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Slater M, Perez-Marcos D, Ehrsson HH, Sanchez-Vives MV. Inducing illusory ownership of a virtual body. Front Neurosci. 2009;3(2):214–20.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Banakou D, Groten R, Slater M. Illusory ownership of a virtual child body causes overestimation of object sizes and implicit attitude changes. Proc Natl Acad Sci U S A. 2013;110(31):12846–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Yee N, Bailenson J. The proteus effect: the effect of transformed self-representation on behavior. Human Commun Res. 2007;33(3):271–90.

    Article  Google Scholar 

  22. Slater M. Measuring presence: a response to the witmer and singer presence questionnaire. Presence. 1999;8(5):560–5.

    Article  Google Scholar 

  23. Rand D, Kizony R, Feintuch U, Katz N, Josman N, Rizzo A, et al. Comparison of two VR platforms for rehabilitation: video capture versus HMD. Presence. 2005;14(2):147–60.

    Article  Google Scholar 

  24. Rand D, Kizony R, Weiss PT. The Sony PlayStation II EyeToy: low-cost virtual reality for use in rehabilitation. J Neurol Phys Ther. 2008;32(4):155–63.

    Article  PubMed  Google Scholar 

  25. Perez-Marcos D, Sanchez-Vives M, Slater M. Is my hand connected to my body? The impact of body continuity and arm alignment on the virtual hand illusion. Cogn Neurodyn. 2012;6(4):295–305.

    Article  PubMed  Google Scholar 

  26. Schmidt RA, editor. Motor learning principles for physical therapy. Contemporary management of motor control problems: proceedings of the II STEP conference. Alexandria: Foundation for Physical Therapy; 1991.

    Google Scholar 

  27. Wulf G, Shea C, Lewthwaite R. Motor skill learning and performance: a review of influential factors. Med Educ. 2010;44(1):75–84.

    Article  PubMed  Google Scholar 

  28. Deutsch JE, Merians AS, Adamovich S, Poizner H, Burdea GC. Development and application of virtual reality technology to improve hand use and gait of individuals post-stroke. Restor Neurol Neurosci. 2004;22(3–5):371–86.

    PubMed  Google Scholar 

  29. Holden MK. Virtual environments for motor rehabilitation: review. Cyberpsychol Behav. 2005;8(3):187–211.

    Article  PubMed  Google Scholar 

  30. Deutsch JE, Brettler A, Smith C, Welsh J, John R, Guarrera-Bowlby P, et al. Nintendo wii sports and wii fit game analysis, validation, and application to stroke rehabilitation. Top Stroke Rehabil. 2011;18(6):701–19.

    Article  PubMed  Google Scholar 

  31. Fluet GG, Deutsch JE. Virtual reality for sensorimotor rehabilitation post-stroke: the promise and current state of the field. Curr Phys Med Rehabil Rep. 2013;1(1):9–20.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Levin MF, Weiss PL, Keshner EA. Emergence of virtual reality as a tool for upper limb rehabilitation: incorporation of motor control and motor learning principles. Phys Ther. 2015;95(3):415–25.

    Article  PubMed  Google Scholar 

  33. Laver KE, George S, Thomas S, Deutsch JE, Crotty M. Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev. 2015;2:523–30.

    Google Scholar 

  34. Levac D, Sveistrup H. Motor learning and virtual reality. In: Weiss PL, Keshner EA, Levin MF, editors. Virtual reality for physical and motor rehabilitation. New York: Springer; 2014.

    Google Scholar 

  35. Kleim JA, Barbay S, Nudo RJ. Functional reorganization of the rat motor cortex following motor skill learning. J Neurophysiol. 1998;80(6):3321–5.

    CAS  PubMed  Google Scholar 

  36. Janssen H, Bernhardt J, Collier JM, Sena ES, McElduff P, Attia J, et al. An enriched environment improves sensorimotor function post-ischemic stroke. Neurorehabil Neural Repair. 2010;24(9):802–13.

    Article  PubMed  Google Scholar 

  37. Janssen H, Ada L, Bernhardt J, McElduff P, Pollack M, Nilsson M, et al. An enriched environment increases activity in stroke patients undergoing rehabilitation in a mixed rehabilitation unit: a pilot non-randomized controlled trial. Disabil Rehabil. 2014;36(3):255–62.

    Article  PubMed  Google Scholar 

  38. Sigrist R, Rauter G, Riener R, Wolf P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon Bull Rev. 2013;20(1):21–53.

    Article  PubMed  Google Scholar 

  39. Winstein CJ. Knowledge of results and motor learning – implications for physical therapy. Phys Ther. 1991;71(2):140–9.

    CAS  PubMed  Google Scholar 

  40. Klinger E, Cherni H, Joseph P-A. Impact of contextual additional stimuli on the performance in a virtual activity of daily living (vADL) among patients with brain injury and controls. Int J Disabil Human Dev. 2014;13(3):377–82.

    Google Scholar 

  41. Molier BI, Van Asseldonk EH, Hermens HJ, Jannink MJ. Nature, timing, frequency and type of augmented feedback; does it influence motor relearning of the hemiparetic arm after stroke? A systematic review. Disabil Rehabil. 2010;32(22):1799–809.

    Article  PubMed  Google Scholar 

  42. Mirelman A, Bonato P, Deutsch JE. Effects of training with a robot-virtual reality system compared with a robot alone on the gait of individuals after stroke. Stroke. 2009;40(1):169–74.

    Article  PubMed  Google Scholar 

  43. Subramanian SK, Lourenco CB, Chilingaryan G, Sveistrup H, Levin MF. Arm motor recovery using a virtual reality intervention in chronic stroke: randomized control trial. Neurorehabil Neural Repair. 2013;27(1):13–23.

    Article  PubMed  Google Scholar 

  44. Holden M, Todorov E, Callahan J, Bizzi E. Virtual environment training improves motor performance in two patients with stroke: case report. J Neurol Phys Ther. 1999;23(2):57–67.

    Google Scholar 

  45. Schmidt RA. Motor learning and performance: a situation-based learning approach. Champaign: Human Kinetics; 2008.

    Google Scholar 

  46. Magill RA. Motor learning and control: current concepts and applications. 9th ed. New York: McGraw Hill; 2007. 466 p.

    Google Scholar 

  47. Lam P, Hebert D, Boger J, Lacheray H, Gardner D, Apkarian J, et al. A haptic-robotic platform for upper-limb reaching stroke therapy: preliminary design and evaluation results. J Neuroeng Rehabil. 2008;5(1):15.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Colomer C, Llorens R, Noé E, Alcañiz M. Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke. J Neuroeng Rehabil. 2016;13:45.

    Google Scholar 

  49. Pichiorri F, Morone G, Petti M, Toppi J, Pisotta I, Molinari M, et al. Brain–computer interface boosts motor imagery practice during stroke recovery. Ann Neurol. 2015;77(5):851–65.

    Article  PubMed  Google Scholar 

  50. Kizony R, Levin MF, Hughey L, Perez C, Fung J. Cognitive load and dual-task performance during locomotion poststroke: a feasibility study using a functional virtual environment. Phys Ther. 2010;90(2):252–60.

    Article  PubMed  Google Scholar 

  51. Adams RJ, Lichter MD, Krepkovich ET, Ellington A, White M, Diamond PT. Assessing upper extremity motor function in practice of virtual activities of daily living. IEEE Trans Neural Syst Rehabil Eng. 2015;23(2):287–96.

    Article  PubMed  Google Scholar 

  52. Cameirão MS, Bermúdez i Badia S, Duarte E, Verschure P. Neurorehabilitation using the virtual reality based rehabilitation gaming system: methodology, design, psychometrics, usability and validation. J Neuroeng Rehabil. 2010;7:48.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Shin J-H, Ryu H, Jang SH. A task-specific interactive game-based virtual reality rehabilitation system for patients with stroke: a usability test and two clinical experiments. J Neuroreng Rehabil. 2014;11(1):32.

    Article  Google Scholar 

  54. Yang YR, Tsai MP, Chuang TY, Sung WH, Wang RY. Virtual reality-based training improves community ambulation in individuals with stroke: a randomized controlled trial. Gait Posture. 2008;28(2):201–6.

    Article  PubMed  Google Scholar 

  55. Fung J, Richards CL, Malouin F, McFadyen BJ, Lamontagne A. A treadmill and motion coupled virtual reality system for gait training post-stroke. Cyberpsychol Behav. 2006;9(2):157–62.

    Article  PubMed  Google Scholar 

  56. Fung J, Perez CF, editors. Sensorimotor enhancement with a mixed reality system for balance and mobility rehabilitation. Engineering in medicine and biology society, EMBC, 2011 annual international conference of the IEEE, IEEE, Boston, MA, 2011.

    Google Scholar 

  57. You SH, Jang SH, Kim Y-H, Hallett M, Ahn SH, Kwon Y-H, et al. Virtual reality–induced cortical reorganization and associated locomotor recovery in chronic stroke an experimenter-blind randomized study. Stroke. 2005;36(6):1166–71.

    Article  PubMed  Google Scholar 

  58. Jaffe DL, Brown DA, Pierson-Carey CD, Buckley EL, Lew HL. Stepping over obstacles to improve walking in individuals with poststroke hemiplegia. J Rehabil Res Dev. 2004;41(3A):283–92.

    Article  PubMed  Google Scholar 

  59. Kwakkel G, van Peppen R, Wagenaar RC, Wood Dauphinee S, Richards C, Ashburn A, et al. Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke. 2004;35(11):2529–39.

    Article  PubMed  Google Scholar 

  60. Schmidt RA, Lee T. Motor control and learning. 5th Revised edition. Champaign: Human Kinetics Ltd; 2011.

    Google Scholar 

  61. Kleim JA, Jones TA. Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. J Speech Lang Hear Res. 2008;51(1):S225–39.

    Article  PubMed  Google Scholar 

  62. Rand D, Givon N, Weingarden H, Nota A, Zeilig G. Eliciting upper extremity purposeful movements using video games: a comparison with traditional therapy for stroke rehabilitation. Neurorehabil Neural Repair. 2014;28(8):733–9.

    Article  PubMed  Google Scholar 

  63. 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;123(2):133–41.

    Article  CAS  PubMed  Google Scholar 

  64. Dancause N, Nudo RJ. Shaping plasticity to enhance recovery after injury. Prog Brain Res. 2011;192:273–95.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Llorens R, Noe E, Colomer C, Alcaniz M. Effectiveness, usability, and cost-benefit of a virtual reality-based telerehabilitation program for balance recovery after stroke: a randomized controlled trial. Arch Phys Med Rehabil. 2015;96(3):418–25.

    Article  PubMed  Google Scholar 

  66. Cameirão M, Bermúdez i Badia S, Duarte E, Verschure PF. Virtual reality based rehabilitation speeds up functional recovery of the upper extremities after stroke: a randomized controlled pilot study in the acute phase of stroke using the rehabilitation gaming system. Restor Neurol Neurosci. 2011;29(5):287–98.

    Google Scholar 

  67. Adamovich SV, Fluet GG, Merians AS, Mathai A, Qiu Q. Incorporating haptic effects into three-dimensional virtual environments to train the hemiparetic upper extremity. IEEE Trans Neural Syst Rehabil Eng. 2009;17(5):512–20.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Fluet GG, Merians AS, Qiu 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: a case report. J Neurol Phys Ther. 2012;36(2):79–86.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Homberg V. Evidence based medicine in neurological rehabilitation – a critical review. Acta Neurochir Suppl. 2005;93:3–14.

    Article  CAS  PubMed  Google Scholar 

  70. Ryan RM, Deci EL. Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp Educ Psychol. 2000;25(1):54–67.

    Article  PubMed  Google Scholar 

  71. Wouters P, Van Nimwegen C, Van Oostendorp H, Van Der Spek ED. A meta-analysis of the cognitive and motivational effects of serious games. J Educ Psychol. 2013;105(2):249.

    Article  Google Scholar 

  72. Linehan C, Kirman B, Lawson S, Chan G, editors. Practical, appropriate, empirically-validated guidelines for designing educational games. Proceedings of the SIGCHI conference on human factors in computing systems; ACM; New York, NY, 2011.

    Google Scholar 

  73. Garris R, Ahlers R, Driskell JE. Games, motivation, and learning: a research and practice model. Simul Gaming. 2002;33(4):441–67.

    Article  Google Scholar 

  74. Faria A, Vourvopoulos A, Cameirão M, Fernandes J, i Badia SB, editors. An integrative virtual reality cognitive-motor intervention approach in stroke rehabilitation: a pilot study. 10th international conference disability, virtual reality & associated technologies, Gothenburg, Sweden, 2014.

    Google Scholar 

  75. Rabin BA, Burdea GC, Roll DT, Hundal JS, Damiani F, Pollack S. Integrative rehabilitation of elderly stroke survivors: the design and evaluation of the BrightArm™. Disabil Rehabil Assist Technol. 2012;7(4):323–35.

    Article  PubMed  Google Scholar 

  76. Cirstea CM, Ptito A, Levin MF. Feedback and cognition in arm motor skill reacquisition after stroke. Stroke. 2006;37(5):1237–42.

    Article  CAS  PubMed  Google Scholar 

  77. Kilduski NC, Rice MS. Qualitative and quantitative knowledge of results: effects on motor learning. Am J Occup Ther. 2003;57(3):329–36.

    Article  PubMed  Google Scholar 

  78. Rosati G, Rodà A, Avanzini F, Masiero S. On the role of auditory feedback in robot-assisted movement training after stroke: review of the literature. Comp Int Neurosci. 2013;2013:11.

    Google Scholar 

  79. Lauber B, Keller M. Improving motor performance: selected aspects of augmented feedback in exercise and health. Eur J Sport Sci. 2014;14(1):36–43.

    Article  PubMed  Google Scholar 

  80. Cameron J, Banko KM, Pierce WD. Pervasive negative effects of rewards on intrinsic motivation: the myth continues. Behav Anal. 2001;24(1):1.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Malone T, Lepper M. Making Learning Fun: A Taxonomy of Intrinsic Motivation for Learning in Snow, RE, and Farr, MJ (eds.) Aptitude. Learning, and Instruction (Hillsdale, NJ: Lawrence Earlbaum, 1987), 1987;3:223–53.

    Google Scholar 

  82. Yerkes RM, Dodson JD. The relation of strength of stimulus to rapidity of habit-formation. J Comp Neurol Psychol. 1908;18(5):459–82.

    Article  Google Scholar 

  83. Duffy E. Activation and behavior. New York: Wiley; 1962.

    Google Scholar 

  84. Malmo RB. Activation: a neuropsychological dimension. Psychol Rev. 1959;66(6):367.

    Article  CAS  PubMed  Google Scholar 

  85. Csikszentmihalyi M. In: Jossey-Bass, editor. Beyond boredom and anxiety: experiencing flow in work and play. San Francisco: Jossey-Bass; 1975.

    Google Scholar 

  86. Von Ahn L, Dabbish L. Designing games with a purpose. Commun ACM. 2008;51(8):58–67.

    Google Scholar 

  87. Bermúdez i Badia S, Cameirao M. The Neurorehabilitation Training Toolkit (NTT): a novel worldwide accessible motor training approach for at-home rehabilitation after stroke. Stroke Res Treat, vol. 2012, Article ID 802157, 13 pages, 2012. doi:10.1155/2012/802157.

    Google Scholar 

  88. Borghese NA, Pirovano M, Lanzi PL, Wüest S, de Bruin ED. Computational intelligence and game design for effective at-home stroke rehabilitation. Game Health. 2013;2(2):81–8.

    Article  Google Scholar 

  89. Bronner S, Pinsker R, Noah JA. Physiological and psychophysiological responses in experienced players while playing different dance exer-games. Comput Hum Behav. 2015;51:34–41.

    Article  Google Scholar 

  90. Gamito P, Oliveira J, Coelho C, Morais D, Lopes P, Pacheco J, et al. Cognitive training on stroke patients via virtual reality-based serious games. Disabil Rehabil. 2015:1–4.

    Google Scholar 

  91. Vourvopoulos A, Faria AL, Ponnam K, Bermudez i Badia S, editors. Rehab City: design and validation of a cognitive assessment and rehabilitation tool through gamified simulations of activities of daily living. Proceedings of the 11th conference on advances in computer entertainment technology; ACM; New York, NY, 2014.

    Google Scholar 

  92. Merians AS, Fluet GG, Qiu Q, Saleh S, Lafond I, Davidow A, et al. Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis. J Neuroeng Rehabil. 2011;8:27.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Ada L, Canning C, Carr J, Kilbreath S, Shepherd R. Task-specific training of reaching and manipulation. Adv Psychol. 1994;105:239–65.

    Article  Google Scholar 

  94. Viau A, Feldman AG, McFadyen BJ, Levin MF. Reaching in reality and virtual reality: a comparison of movement kinematics in healthy subjects and in adults with hemiparesis. J Neuroeng Rehabil. 2004;1(1):11.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Subramanian S, Knaut LA, Beaudoin C, McFadyen BJ, Feldman AG, Levin MF. Virtual reality environments for post-stroke arm rehabilitation. J Neuroeng Rehabil. 2007;4:20.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Knaut LA, Subramanian SK, McFadyen BJ, Bourbonnais D, Levin MF. Kinematics of pointing movements made in a virtual versus a physical 3-dimensional environment in healthy and stroke subjects. Arch Phys Med Rehabil. 2009;90(5):793–802.

    Article  PubMed  Google Scholar 

  97. Levin MF, Magdalon EC, Michaelsen SM, Quevedo A. Quality of grasping and the role of haptics in a 3D immersive virtual reality environment in individuals with stroke. IEEE Trans Neural Syst Rehabil Eng. 2015;23:1047–55; PP(99):1.

    Article  PubMed  Google Scholar 

  98. van den Hoogen W, Feys P, Lamers I, Coninx K, Notelaers S, Kerkhofs L, et al. Visualizing the third dimension in virtual training environments for neurologically impaired persons: beneficial or disruptive? J Neuroeng Rehabil. 2012;9(1):73.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Fluet G, Merians A, Qiu Q, Adamovich S, editors. Sensorimotor training in virtual environments produces similar outcomes to real world training with greater efficiency. Virtual Rehabilitation (ICVR), 2013 international conference on; IEEE; Philadelphia, PA, 2013.

    Google Scholar 

  100. Weiss PL, Rand D, Katz N, Kizony R. Video capture virtual reality as a flexible and effective rehabilitation tool. J Neuroeng Rehabil. 2004;1(1):12.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Hondori HM, Khademi M, McKenzie A, Dodakian L, Lopes CV, Cramer SC. Utility of augmented reality in relation to virtual reality in stroke rehabilitation. Stroke. 2014;45:1.

    Article  Google Scholar 

  102. Thaut MH, McIntosh GC, Hoemberg V. Neurobiological foundations of neurologic music therapy: rhythmic entrainment and the motor system. Front Psychol. 2014;5:1185–95.

    Google Scholar 

  103. Powell W. Virtually walking: factors influencing walking and perception of walking in treadmill-mediated virtual reality to support rehabilitation. University of Portsmouth; Portsmouth, UK, 2011.

    Google Scholar 

  104. Friedman N, Chan V, Zondervan D, Bachman M, Reinkensmeyer DJ, editors. MusicGlove: motivating and quantifying hand movement rehabilitation by using functional grips to play music. Engineering in medicine and biology society, EMBC, 2011 annual international conference of the IEEE, IEEE, Boston, MA, 2011.

    Google Scholar 

  105. Brütsch K, Koenig A, Zimmerli L, Mérillat-Koeneke S, Riener R, Jäncke L, et al. Virtual reality for enhancement of robot-assisted gait training in children with neurological gait disorders. J Rehabil Med. 2011;43(6):493–9.

    Article  PubMed  Google Scholar 

  106. Adamovich S, Fluet G, Mathai A, Qiu Q, Lewis J, Merians A. Design of a complex virtual reality simulation to train finger motion for persons with hemiparesis: a proof of concept study. J Neuroeng Rehabil. 2009;6:28.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Wellner M, Thüring T, Smajic E, von Zitzewitz J, Duschau-Wicke A, Riener R. Obstacle crossing in a virtual environment with the rehabilitation gait robot LOKOMAT. Stud Health Technol Inform. 2006;125:497–9.

    Google Scholar 

  108. Huegel JC, O’Malley MK, editors. Progressive haptic and visual guidance for training in a virtual dynamic task. Haptics symposium, 2010 IEEE, Waltham, MA, 25–26 Mar 2010.

    Google Scholar 

  109. Huang FC, Gillespie RB, Kuo AD. Visual and haptic feedback contribute to tuning and online control during object manipulation. J Mot Behav. 2007;39(3):179–93.

    Article  PubMed  Google Scholar 

  110. Schweighofer N, Choi Y, Winstein C, Gordon J. Task-oriented rehabilitation robotics. Am J Phys Med Rehabil. 2012;91(11):S270–9.

    Article  PubMed  Google Scholar 

  111. Ang KK, Guan C. Brain-computer interface in stroke rehabilitation. J Comp Sci Eng. 2013;7(2):139–46.

    Article  Google Scholar 

  112. Vourvopoulos A, Muñoz J, Bermúdez i Badia S, editors. Optimizing motor imagery neurofeedback through the use of multimodal immersive virtual reality and motor priming. Virtual rehabilitation (ICVR), 2015 international conference on IEEE, Valencia, Spain, 2015.

    Google Scholar 

  113. Prasad G, Herman P, Coyle D, McDonough S, Crosbie J. Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study. J Neuroeng Rehabil. 2010;7(1):60.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain–computer interfaces for communication and control. Clin Neurophysiol. 2002;113(6):767–91.

    Article  PubMed  Google Scholar 

  115. Bütefisch CM, Netz J, Weßling M, Seitz RJ, Hömberg V. Remote changes in cortical excitability after stroke. Brain. 2003;126(2):470–81.

    Article  PubMed  Google Scholar 

  116. Ward NS, Newton JM, Swayne OB, Lee L, Thompson AJ, Greenwood RJ, et al. Motor system activation after subcortical stroke depends on corticospinal system integrity. Brain. 2006;129(3):809–19.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Ward N, Brown M, Thompson A, Frackowiak R. Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain. 2003;126(11):2476–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Carey LM, Abbott DF, Egan GF, O’Keefe GJ, Jackson GD, Bernhardt J, et al. Evolution of brain activation with good and poor motor recovery after stroke. Neurorehabil Neural Repair. 2006;20(1):24–41.

    Article  PubMed  Google Scholar 

  119. Jang SH, You SH, Hallett M, Cho YW, Park C-M, Cho S-H, et al. Cortical reorganization and associated functional motor recovery after virtual reality in patients with chronic stroke: an experimenter-blind preliminary study. Arch Phys Med Rehabil. 2005;86(11):2218–23.

    Article  PubMed  Google Scholar 

  120. Saleh S, Bagce H, Qiu Q, Fluet G, Merians A, Adamovich S, et al. Mechanisms of neural reorganization in chronic stroke subjects after virtual reality training. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:8118–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  121. Orihuela-Espina F, Fernandez del Castillo I, Palafox L, Pasaye E, Sanchez-Villavicencio I, Leder R. Neural reorganization accompanying upper limb motor rehabilitation from stroke with virtual reality-based gesture therapy. Top Stroke Rehabil. 2013;20(3):197–209.

    Article  PubMed  Google Scholar 

  122. Richards LG, Stewart KC, Woodbury ML, Senesac C, Cauraugh JH. Movement-dependent stroke recovery: a systematic review and meta-analysis of TMS and fMRI evidence. Neuropsychologia. 2008;46(1):3–11.

    Article  PubMed  Google Scholar 

  123. Carel C, Loubinoux I, Boulanouar K, Manelfe C, Rascol O, Celsis P, et al. Neural substrate for the effects of passive training on sensorimotor cortical representation: a study with functional magnetic resonance imaging in healthy subjects. J Cereb Blood Flow Metab. 2000;20(3):478–84.

    Article  CAS  PubMed  Google Scholar 

  124. Jang SH, Kim Y-H, Cho S-H, Lee J-H, Park J-W, Kwon Y-H. Cortical reorganization induced by task-oriented training in chronic hemiplegic stroke patients. Neuroreport. 2003;14(1):137–41.

    Article  PubMed  Google Scholar 

  125. Grefkes C, Fink GR. Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches. Brain. 2011;134:1264–76.

    Article  PubMed  PubMed Central  Google Scholar 

  126. Cramer SC. Repairing the human brain after stroke: I. Mechanisms of spontaneous recovery. Ann Neurol. 2008;63(3):272–87.

    Article  PubMed  Google Scholar 

  127. Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Cortical mechanisms of human imitation. Science. 1999;286(5449):2526–8.

    Article  CAS  PubMed  Google Scholar 

  128. Gallese V, Fadiga L, Fogassi L, Rizzolatti G. Action recognition in the premotor cortex. Brain. 1996;119(2):593–609.

    Article  PubMed  Google Scholar 

  129. Grezes J, Decety J. Functional anatomy of execution, mental simulation, observation, and verb generation of actions: a meta-analysis. Hum Brain Mapp. 2001;12(1):1–19.

    Article  CAS  PubMed  Google Scholar 

  130. Rizzolatti G, Craighero L. The mirror-neuron system. Annu Rev Neurosci. 2004;27:169–92.

    Article  CAS  PubMed  Google Scholar 

  131. Buccino G, Solodkin A, Small SL. Functions of the mirror neuron system: implications for neurorehabilitation. Cogn Behav Neurol. 2006;19(1):55–63.

    Article  PubMed  Google Scholar 

  132. Garrison KA, Winstein CJ, Aziz-Zadeh L. The mirror neuron system: a neural substrate for methods in stroke rehabilitation. Neurorehabil Neural Repair. 2010;24(5):404–12.

    Article  PubMed  Google Scholar 

  133. Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, et al. Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study. Eur J Neurosci. 2001;13(2):400–4.

    CAS  PubMed  Google Scholar 

  134. Sale P, Franceschini M. Action observation and mirror neuron network: a tool for motor stroke rehabilitation. Eur J Phys Rehabil Med. 2012;48(2):313–8.

    CAS  PubMed  Google Scholar 

  135. Ertelt D, Small S, Solodkin A, Dettmers C, McNamara A, Binkofski F, et al. Action observation has a positive impact on rehabilitation of motor deficits after stroke. Neuroimaging. 2007;36:164–73.

    Article  Google Scholar 

  136. Maeda F, Kleiner-Fisman G, Pascual-Leone A. Motor facilitation while observing hand actions: specificity of the effect and role of observer’s orientation. J Neurophysiol. 2002;87(3):1329–35.

    PubMed  Google Scholar 

  137. Gazzola V, Rizzolatti G, Wicker B, Keysers C. The anthropomorphic brain: the mirror neuron system responds to human and robotic actions. Neuroimage. 2007;35(4):1674–84.

    Article  CAS  PubMed  Google Scholar 

  138. Ferrari PF, Rozzi S, Fogassi L. Mirror neurons responding to observation of actions made with tools in monkey ventral premotor cortex. J Cogn Neurosci. 2005;17(2):212–26.

    Article  PubMed  Google Scholar 

  139. Modrono C, Navarrete G, Rodríguez-Hernández AF, González-Mora JL. Activation of the human mirror neuron system during the observation of the manipulation of virtual tools in the absence of a visible effector limb. Neurosci Lett. 2013;555:220–4.

    Article  CAS  PubMed  Google Scholar 

  140. August K, Lewis J, Chandar G, Merians A, Biswal B, Adamovich S, editors. FMRI analysis of neural mechanisms underlying rehabilitation in virtual reality: activating secondary motor areas. Engineering in medicine and biology society, 2006. EMBS’06. 28th annual international conference of the IEEE, IEEE, New York, NY, 2006.

    Google Scholar 

  141. Prochnow D, Bermúdez i Badia S, Schmidt J, Duff A, Brunheim S, Kleiser R, et al. A functional magnetic resonance imaging study of visuomotor processing in a virtual reality‐based paradigm: rehabilitation gaming system. Eur J Neurosci. 2013;37(9):1441–7.

    Article  CAS  PubMed  Google Scholar 

  142. Dobkin BH. Brain–computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation. J Physiol. 2007;579(3):637–42.

    Article  CAS  PubMed  Google Scholar 

  143. Grosse-Wentrup M, Mattia D, Oweiss K. Using brain–computer interfaces to induce neural plasticity and restore function. J Neural Eng. 2011;8(2):025004.

    Article  PubMed  PubMed Central  Google Scholar 

  144. Villiger M, Estévez N, Hepp-Reymond M-C, Kiper D, Kollias SS, Eng K, et al. Enhanced activation of motor execution networks using action observation combined with imagination of lower limb movements. PLoS ONE. 2013;8(8):e72403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Bermúdez i Badia S, Garcia Morgade A, Samaha H, Verschure P. Using a hybrid brain computer interface and virtual reality system to monitor and promote cortical reorganization through motor activity and motor imagery training. IEEE Trans Neural Syst Rehabil Eng. 2013;21(2):174–81.

    Article  PubMed  Google Scholar 

  146. Abdollahi F, Rozario SV, Kenyon RV, Patton JL, Case E, Kovic M, et al. Arm control recovery enhanced by error augmentation. IEEE international conference rehabilitation robotics, Zurich, Switzerland, Jun 29–Jul 1 2011;1–6.

    Google Scholar 

  147. Tunik E, Saleh S, Adamovich SV. 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(2):198–207.

    Article  PubMed  PubMed Central  Google Scholar 

  148. Lewis CH, Griffin MJ. Human factors consideration in clinical applications of virtual reality in virtual reality in Neuro-Psycho-Physiology. GIUSEPPE RIVA (Ed.) 1997, 1998 ‘Ios Press: Amsterdam, Netherlands, 1997;35–58.

    Google Scholar 

  149. Ballester BR, Nirme J, Duarte E, Cuxart A, Rodriguez S, Verschure P, et al. The visual amplification of goal-oriented movements counteracts acquired non-use in hemiparetic stroke patients. J Neuroeng Rehabil. 2015;12:50.

    Article  PubMed  PubMed Central  Google Scholar 

  150. Saposnik G, Levin M. Virtual reality in stroke rehabilitation a meta-analysis and implications for clinicians. Stroke. 2011;42(5):1380–6.

    Article  PubMed  Google Scholar 

  151. Henderson A, Korner-Bitensky N, Levin M. Virtual reality in stroke rehabilitation: a systematic review of its effectiveness for upper limb motor recovery. Top Stroke Rehabil. 2007;14(2):52–61.

    Article  PubMed  Google Scholar 

  152. Byl NN, Abrams GM, Pitsch E, Fedulow I, Kim H, Simkins M, et al. Chronic stroke survivors achieve comparable outcomes following virtual task specific repetitive training guided by a wearable robotic orthosis (UL-EXO7) and actual task specific repetitive training guided by a physical therapist. J Hand Ther. 2013;26(4):343–52.

    Article  PubMed  Google Scholar 

  153. Fluet GG, Merians AS, Qiu Q, Rohafaza M, VanWingerden AM, Adamovich S. Does training with traditionally presented and virtually simulated tasks elicit differing changes in object interaction kinematics in persons with upper extremity hemiparesis? Top Stroke Rehabil. 2015;22(3):176–84.

    Article  PubMed  PubMed Central  Google Scholar 

  154. Turolla A, Daud Albasini OA, Oboe R, Agostini M, Tonin P, Paolucci S, et al. Haptic-based neurorehabilitation in poststroke patients: a feasibility prospective multicentre trial for robotics hand rehabilitation. Comput Math Methods Med. 2013: pp 1–12.

    Google Scholar 

  155. Fluet GG, Merians AS, Qiu Q, Davidow A, Adamovich SV. Comparing integrated training of the hand and arm with isolated training of the same effectors in persons with stroke using haptically rendered virtual environments, a randomized clinical trial. J Neuroeng Rehabil. 2014;11(1):126.

    Article  PubMed  PubMed Central  Google Scholar 

  156. In TS, Jung KS, Lee SW, Song CH. Virtual reality reflection therapy improves motor recovery and motor function in the upper extremities of people with chronic stroke. J Phys Ther Sci. 2012;24(4):339–43.

    Article  Google Scholar 

  157. Kottink AI, Prange GB, Krabben T, Rietman JS, Buurke JH. Gaming and conventional exercises for improvement of arm function after stroke: a randomized controlled pilot study. Games Health. 2014;3(3):184–91.

    Article  Google Scholar 

  158. Turolla A, Dam M, Ventura L, Tonin P, Agostini M, Zucconi C, et al. Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J Neuroeng Rehabil. 2013;10:85.

    Article  PubMed  PubMed Central  Google Scholar 

  159. Lee SJ, Chun MH. Combination transcranial direct current stimulation and virtual reality therapy for upper extremity training in patients with subacute stroke. Arch Phys Med Rehabil. 2014;95(3):431–8.

    Article  PubMed  Google Scholar 

  160. Cameirão MS, Bermúdez i Badia S, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke. 2012;43(10):2720–8.

    Article  PubMed  Google Scholar 

  161. Ang KK, Guan C, Chua KSG, Ang BT, Kuah CWK, Wang C, et al. A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain-computer interface. Clin EEG Neurosci. 2011;42(4):253–8.

    Article  PubMed  Google Scholar 

  162. Cincotti F, Pichiorri F, Arico P, Aloise F, Leotta F, de Vico Fallani F, et al., editors. EEG-based brain-computer interface to support post-stroke motor rehabilitation of the upper limb. Engineering in medicine and biology society (EMBC), 2012 annual international conference of the IEEE, IEEE, San Diego, CA, 2012.

    Google Scholar 

  163. Ang KK, Guan C, Sui Geok Chua K, Ang BT, Kuah C, Wang C, et al., editors. A clinical study of motor imagery-based brain-computer interface for upper limb robotic rehabilitation. Engineering in medicine and biology society, 2009. EMBC 2009. annual international conference of the IEEE, IEEE, Minneapolis, MN, 2009.

    Google Scholar 

  164. Ang KK, Guan C, Sui Geok Chua K, Ang BT, Kuah C, Wang C, et al., editors. Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback. Engineering in medicine and biology society (EMBC), 2010 annual international conference of the IEEE, IEEE, Buenos Aires, 2010.

    Google Scholar 

  165. Varkuti B, Guan C, Pan Y, Phua KS, Ang KK, Kuah CWK, et al. Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke. Neurorehabil Neural Repair. 2013;27(1):53–62.

    Article  PubMed  Google Scholar 

  166. Weiss PL, Sveistrup H, Rand D, Kizony R. Video capture virtual reality: a decade of rehabilitation assessment and intervention. Phys Ther Rev. 2009;14(5):307–21.

    Article  Google Scholar 

  167. Yavuzer G, Senel A, Atay M, Stam H. “Playstation eyetoy games” improve upper extremity-related motor functioning in subacute stroke: a randomized controlled clinical trial. Eur J Phys Rehabil Med. 2008;44(3):237–44.

    CAS  PubMed  Google Scholar 

  168. da Silva Ribeiro NM, Ferraz DD, Pedreira É, Mascarenha Í, da Silva Pinto AC, Neto MG, et al. Virtual rehabilitation via Nintendo Wii® and conventional physical therapy effectively treat post-stroke hemiparetic patients. Top Stroke Rehabil. 2015;22(4):299–305.

    Article  PubMed  Google Scholar 

  169. Shiner CT, Byblow WD, McNulty PA. Bilateral priming before wii-based movement therapy enhances upper limb rehabilitation and its retention after stroke a case-controlled study. Neurorehabil Neural Repair. 2014;28(9):828–38.

    Article  PubMed  Google Scholar 

  170. Joo LY, Yin TS, Xu D, Thia E, Chia PF, Kuah CWK, et al. A feasibility study using interactive commercial off-the-shelf computer gaming in upper limb rehabilitation in patients after stroke. J Rehabil Med. 2010;42(5):437–41.

    Article  Google Scholar 

  171. Mouawad MR, Doust CG, Max MD, McNulty PA. Wii-based movement therapy to promote improved upper extremity function post-stroke: a pilot study. J Rehabil Med. 2011;43(6):527–33.

    Article  PubMed  Google Scholar 

  172. Paquin K, Ali S, Carr K, Crawley J, McGowan C, Horton S. Effectiveness of commercial video gaming on fine motor control in chronic stroke within community-level rehabilitation. Disabil Rehabil. 2015:1–8.

    Google Scholar 

  173. Saposnik G, Teasell R, Mamdani M, Hall J, McIlroy W, Cheung D, et al. Effectiveness of virtual reality using wii gaming technology in stroke rehabilitation a pilot randomized clinical trial and proof of principle. Stroke. 2010;41(7):1477–84.

    Article  PubMed  PubMed Central  Google Scholar 

  174. Chen M-H, Huang L-L, Lee C-F, Hsieh C-L, Lin Y-C, Liu H, et al. A controlled pilot trial of two commercial video games for rehabilitation of arm function after stroke. Clin Rehabili. 2014:1–9.

    Google Scholar 

  175. Webster D, Celik O. Systematic review of Kinect applications in elderly care and stroke rehabilitation. J Neuroeng Rehabil. 2014;11(1):108.

    Article  PubMed  PubMed Central  Google Scholar 

  176. Pastor I, Hayes HA, Bamberg SJM, editors. A feasibility study of an upper limb rehabilitation system using kinect and computer games. Engineering in medicine and biology society (EMBC), 2012 annual international conference of the IEEE, San Diego, CA, Aug 28–Sept 1 2012.

    Google Scholar 

  177. Bao X, Mao Y, Lin Q, Qiu Y, Chen S, Li L, et al. Mechanism of Kinect-based virtual reality training for motor functional recovery of upper limbs after subacute stroke. Neural Regen Res. 2013;8(31):2904–13.

    PubMed  PubMed Central  Google Scholar 

  178. Lee G. Effects of training using video games on the muscle strength, muscle tone, and activities of daily living of chronic stroke patients. J Phys Ther Sci. 2013;25(5):595.

    Article  PubMed  PubMed Central  Google Scholar 

  179. Booth V, Masud T, Connell L, Bath-Hextall F. The effectiveness of virtual reality interventions in improving balance in adults with impaired balance compared with standard or no treatment: a systematic review and meta-analysis. Clin Rehabil. 2013;7:1319–28.

    Google Scholar 

  180. Deutsch JE, Mirelman A. Virtual reality-based approaches to enable walking for people poststroke. Top Stroke Rehabil. 2007;14(6):45–53.

    Article  CAS  PubMed  Google Scholar 

  181. Darekar A, McFadyen BJ, Lamontagne A, Fung J. Efficacy of virtual reality-based intervention on balance and mobility disorders post-stroke: a scoping review. J Neuroeng Rehabil. 2015;12(1):46.

    Article  PubMed  PubMed Central  Google Scholar 

  182. Barclay-Goddard R, Stevenson T, Poluha W, Moffatt ME, Taback SP. Force platform feedback for standing balance training after stroke. Cochrane Database Syst Rev. 2004;(4):CD004129.

    Google Scholar 

  183. Sveistrup H, McComas J, Thornton M, Marshall S, Finestone H, McCormick A, et al. Experimental studies of virtual reality-delivered compared to conventional exercise programs for rehabilitation. Cyberpsychol Behav. 2003;6(3):245–9.

    Article  PubMed  Google Scholar 

  184. Bisson E, Contant B, Sveistrup H, Lajoie Y. Functional balance and dual-task reaction times in older adults are improved by virtual reality and biofeedback training. Cyberpsychol Behav. 2007;10(1):16–23.

    Article  CAS  PubMed  Google Scholar 

  185. Thornton M, Marshall S, McComas J, Finestone H, McCormick A, Sveistrup H. Benefits of activity and virtual reality based balance exercise programmes for adults with traumatic brain injury: perceptions of participants and their caregivers. Brain Inj. 2005;19(12):989–1000.

    Article  CAS  PubMed  Google Scholar 

  186. Gil-Gomez JA, Llorens R, Alcaniz M, Colomer C. Effectiveness of a wii balance board-based system (eBaViR) for balance rehabilitation: a pilot randomized clinical trial in patients with acquired brain injury. J Neuroeng Rehabil. 2011;8:30.

    Article  PubMed  PubMed Central  Google Scholar 

  187. Lloréns R, Albiol S, Gil-Gómez J-A, Alcañiz M, Colomer C, Noé E. Balance rehabilitation using custom-made Wii Balance Board exercises: clinical effectiveness and maintenance of gains in an acquired brain injury population. Int J Disabil Human Dev. 2014;3:327–32.

    Google Scholar 

  188. Cikajlo I, Rudolf M, Goljar N, Burger H, Matjačić Z. Telerehabilitation using virtual reality task can improve balance in patients with stroke. Disabil Rehabil. 2012;34(1):13–8.

    Article  PubMed  Google Scholar 

  189. Krpic A, Savanovic A, Cikajlo I. Telerehabilitation: remote multimedia-supported assistance and mobile monitoring of balance training outcomes can facilitate the clinical staff’s effort. Int J Rehabil Res. 2013;36(2):162–71.

    Article  PubMed  Google Scholar 

  190. Cho KH, Lee WH. Virtual walking training program using a real-world video recording for patients with chronic stroke: a pilot study. Am J Phys Med Rehabil. 2013;92(5):371–84.

    Article  PubMed  Google Scholar 

  191. Darter BJ, Wilken JM. Gait training with virtual reality-based real-time feedback: improving gait performance following transfemoral amputation. Phys Ther. 2011;91(9):1385–94.

    Article  PubMed  Google Scholar 

  192. Yang S, Hwang WH, Tsai YC, Liu FK, Hsieh LF, Chern JS. Improving balance skills in patients who had stroke through virtual reality treadmill training. Am J Phys Med Rehabil. 2011;90(12):969–78.

    Article  PubMed  Google Scholar 

  193. Walker ML, Ringleb SI, Maihafer GC, Walker R, Crouch JR, Van Lunen B, et al. Virtual reality-enhanced partial body weight-supported treadmill training poststroke: feasibility and effectiveness in 6 subjects. Arch Phys Med Rehabil. 2010;91(1):115–22.

    Article  PubMed  Google Scholar 

  194. Llorens R, Gil-Gomez JA, Alcaniz M, Colomer C, Noe E. Improvement in balance using a virtual reality-based stepping exercise: a randomized controlled trial involving individuals with chronic stroke. Clin Rehabil. 2015;29(3):261–8.

    Article  PubMed  Google Scholar 

  195. Flynn S, Palma P, Bender A. Feasibility of using the Sony PlayStation 2 gaming platform for an individual poststroke: a case report. J Neurol Phys Ther. 2007;31(4):180–9.

    Article  PubMed  Google Scholar 

  196. Deutsch JE, Robbins D, Morrison J, Bowlby PG. Wii-based compared to standard of care balance and mobility rehabilitation for two individuals post-stroke. 2009 virtual rehabilitation international conference 2009. Haifa, Israel, p. 117–20.

    Google Scholar 

  197. Fritz SL, Peters DM, Merlo AM, Donley J. Active video-gaming effects on balance and mobility in individuals with chronic stroke: a randomized controlled trial. Top Stroke Rehabil. 2013;20(3):218–25.

    Article  PubMed  Google Scholar 

  198. Cho KH, Lee KJ, Song CH. Virtual-reality balance training with a video-game system improves dynamic balance in chronic stroke patients. Tohoku J Exp Med. 2012;228(1):69–74.

    Article  PubMed  Google Scholar 

  199. Barcala L, Grecco LA, Colella F, Lucareli PR, Salgado AS, Oliveira CS. Visual biofeedback balance training using wii fit after stroke: a randomized controlled trial. J Phys Ther Sci. 2013;25(8):1027–32.

    Article  PubMed  PubMed Central  Google Scholar 

  200. Hung JW, Chou CX, Hsieh YW, Wu WC, Yu MY, Chen PC, et al. Randomized comparison trial of balance training by using exergaming and conventional weight-shift therapy in patients with chronic stroke. Arch Phys Med Rehabil. 2014;95(9):1629–37.

    Article  PubMed  Google Scholar 

  201. Deutsch JE, Bowlby PG, Kafri M, editors. Effects of optimal standard of care compared with interactive video gaming-based balance and mobility training for individuals post-stroke. World congress of physical therapy, Amsterdam, 2011.

    Google Scholar 

  202. Morone G, Tramontano M, Iosa M, Shofany J, Iemma A, Musicco M, et al. The efficacy of balance training with video game-based therapy in subacute stroke patients: a randomized controlled trial. Biomed Res Int, vol. 2014, Article ID 580861, 6 pages, 2014. doi:10.1155/2014/580861.

    Google Scholar 

  203. Rajaratnam B, Gui KaiEn J, Lee JiaLin K, SweeSin K, Sim FenRu S, Enting L, et al. Does the inclusion of virtual reality games within conventional rehabilitation enhance balance retraining after a recent episode of stroke? Rehabil Res Pract, vol. 2013, Article ID 649561, 6 pages, 2013. doi:10.1155/2013/649561.

    Google Scholar 

  204. Bower KJ, Clark RA, McGinley JL, Martin CL, Miller KJ. Clinical feasibility of the nintendo wii for balance training post-stroke: a phase II randomized controlled trial in an inpatient setting. Clin Rehabil. 2014;28(9):912–23.

    Article  PubMed  Google Scholar 

  205. Kizony R, Weiss PL. Virtual reality rehabilitation for all: vivid GX versus Sony PlayStation II EyeToy. 5th international conference on disability, virtual reality and associated technologies, Oxford, 2004. p. 87–94.

    Google Scholar 

  206. Singh DK, Mohd Nordin NA, Abd Aziz NA, Lim BK, Soh LC. Effects of substituting a portion of standard physiotherapy time with virtual reality games among community-dwelling stroke survivors. BMC Neurol. 2013;13:199.

    Article  PubMed  PubMed Central  Google Scholar 

  207. Gordon NF, Gulanick M, Costa F, Fletcher G, Franklin BA, Roth EJ, et al. Physical activity and exercise recommendations for stroke survivors: an American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical Activity, and Metabolism; and the Stroke Council. Circulation. 2004;109(16):2031–41.

    Article  PubMed  Google Scholar 

  208. Rimmer JH, Wang E, Smith D. Barriers associated with exercise and community access for individuals with stroke. J Rehabil Res Dev. 2008;45(2):315–22.

    Article  PubMed  Google Scholar 

  209. Ranky RG, Sivak ML, Lewis JA, Gade VK, Deutsch JE, Mavroidis C. Modular mechatronic system for stationary bicycles interfaced with virtual environment for rehabilitation. J Neuroeng Rehabil. 2014;11:93.

    Article  PubMed  PubMed Central  Google Scholar 

  210. Deutsch JE, Myslinski MJ, Kafri M, Ranky R, Sivak M, Mavroidis C, et al. Feasibility of virtual reality augmented cycling for health promotion of people poststroke. J Neurol Phys Ther. 2013;37(3):118–24.

    Article  PubMed  Google Scholar 

  211. Kafri M, Myslinski MJ, Gade VK, Deutsch JE. Energy expenditure and exercise intensity of interactive video gaming in individuals poststroke. Neurorehabil Neural Repair. 2014;28(1):56–65.

    Article  PubMed  Google Scholar 

  212. Hurkmans HL, Ribbers GM, Streur-Kranenburg MF, Stam HJ, van den Berg-Emons RJ. Energy expenditure in chronic stroke patients playing Wii sports: a pilot study. J Neuroeng Rehabil. 2011;8:38.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sergi Bermúdez i Badia Eng, PhD .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing

About this chapter

Cite this chapter

Bermúdez i Badia, S., Fluet, G.G., Llorens, R., Deutsch, J.E. (2016). Virtual Reality for Sensorimotor Rehabilitation Post Stroke: Design Principles and Evidence. In: Reinkensmeyer, D., Dietz, V. (eds) Neurorehabilitation Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-28603-7_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-28603-7_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28601-3

  • Online ISBN: 978-3-319-28603-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics