Digital Neurorehabilitation: Virtual Reality, Robotics and Neuroplasticity After Stroke
DOI:
https://doi.org/10.64784/283Palabras clave:
Stroke; neurorehabilitation; virtual reality; robotics; neuroplasticity; motor recovery; functional independence.Resumen
Stroke is a leading cause of long-term neurological disability, frequently producing persistent motor impairment, loss of independence, and limitations in social participation. Virtual reality and robot-assisted rehabilitation have emerged as strategies for increasing treatment intensity, repetition, task specificity, feedback, and patient engagement. This study aimed to analyze their effectiveness in promoting neuroplasticity and improving motor and functional outcomes in adults after stroke. A structured integrative literature review based on the Scientific Method and PRISMA 2020 principles was conducted using PubMed/MEDLINE, the Cochrane Library, Scopus, Web of Science, IEEE Xplore, PEDro, and official journal databases. Twenty publications were selected, including systematic reviews, meta-analyses, randomized controlled trials, narrative reviews, and a clinical practice guideline. Ten publications were systematic reviews or meta-analyses; five presented predominantly favorable findings, four reported conditional or mixed results, and one found no clear additional benefit. Virtual reality was associated with selected improvements in upper-limb motor function, dexterity, functional independence, quality of life, cortical activation, and functional connectivity. Robot-assisted rehabilitation provided intensive and measurable movement practice and improved selected impairment-based outcomes, although its superiority over dose-matched conventional rehabilitation was inconsistent. Improvements in motor control and strength did not always translate into greater independence or spontaneous use of the affected limb in daily life. The findings indicate that digital neurorehabilitation is most effective when it provides active, repetitive, intensive, task-specific, progressively challenging, and feedback-rich training. Virtual reality and robotics should be integrated as complementary components of conventional rehabilitation rather than universal replacements. Further randomized trials with standardized protocols, equivalent treatment doses, clinically meaningful outcomes, direct neuroplasticity measurements, safety assessment, and long-term follow-up are required.
Referencias
• Bertani, R., Melegari, C., De Cola, M. C., Bramanti, A., Bramanti, P., & Calabrò, R. S. (2017). Effects of robot-assisted upper limb rehabilitation in stroke patients: A systematic review with meta-analysis. Neurological Sciences, 38(9), 1561–1569. https://doi.org/10.1007/s10072-017-2995-5
• Chien, W.-T., Chong, Y.-Y., Tse, M.-K., Chien, C.-W., & Cheng, H.-Y. (2020). Robot-assisted therapy for upper-limb rehabilitation in subacute stroke patients: A systematic review and meta-analysis. Brain and Behavior, 10(8), e01742. https://doi.org/10.1002/brb3.1742
• Di Pino, G., Pellegrino, G., Assenza, G., Capone, F., Ferreri, F., Formica, D., Ranieri, F., Tombini, M., Ziemann, U., Rothwell, J. C., & Di Lazzaro, V. (2014). Modulation of brain plasticity in stroke: A novel model for neurorehabilitation. Nature Reviews Neurology, 10(10), 597–608. https://doi.org/10.1038/nrneurol.2014.162
• Dimyan, M. A., & Cohen, L. G. (2011). Neuroplasticity in the context of motor rehabilitation after stroke. Nature Reviews Neurology, 7(2), 76–85. https://doi.org/10.1038/nrneurol.2010.200
• Hao, J., Xie, H., Harp, K., Chen, Z., & Siu, K.-C. (2022). Effects of virtual reality intervention on neural plasticity in stroke rehabilitation: A systematic review. Archives of Physical Medicine and Rehabilitation, 103(3), 523–541. https://doi.org/10.1016/j.apmr.2021.06.024
• Huang, C.-Y., Chiang, W.-C., Yeh, Y.-C., Fan, S.-C., Yang, W.-H., Kuo, H.-C., & Li, P.-C. (2022). Effects of virtual reality-based motor control training on inflammation, oxidative stress, neuroplasticity and upper limb motor function in patients with chronic stroke: A randomized controlled trial. BMC Neurology, 22, Article 21. https://doi.org/10.1186/s12883-021-02547-4
• Krakauer, J. W., Carmichael, S. T., Corbett, D., & Wittenberg, G. F. (2012). Getting neurorehabilitation right: What can be learned from animal models? Neurorehabilitation and Neural Repair, 26(8), 923–931. https://doi.org/10.1177/1545968312440745
• Langhorne, P., Bernhardt, J., & Kwakkel, G. (2011). Stroke rehabilitation. The Lancet, 377(9778), 1693–1702. https://doi.org/10.1016/S0140-6736(11)60325-5
• Laver, K. E., Lange, B., George, S., Deutsch, J. E., Saposnik, G., Chapman, M., & Crotty, M. (2025). Virtual reality for stroke rehabilitation. Cochrane Database of Systematic Reviews, 2025(6), CD008349. https://doi.org/10.1002/14651858.CD008349.pub5
• Li, S. (2017). Spasticity, motor recovery, and neural plasticity after stroke. Frontiers in Neurology, 8, Article 120. https://doi.org/10.3389/fneur.2017.00120
• Mang, C. S., Campbell, K. L., Ross, C. J. D., & Boyd, L. A. (2013). Promoting neuroplasticity for motor rehabilitation after stroke: Considering the effects of aerobic exercise and genetic variation on brain-derived neurotrophic factor. Physical Therapy, 93(12), 1707–1716. https://doi.org/10.2522/ptj.20130053
• Mehrholz, J., Pollock, A., Pohl, M., Kugler, J., & Elsner, B. (2020). Systematic review with network meta-analysis of randomized controlled trials of robotic-assisted arm training for improving activities of daily living and upper limb function after stroke. Journal of NeuroEngineering and Rehabilitation, 17, Article 83. https://doi.org/10.1186/s12984-020-00715-0
• Soleimani, M., Ghazisaeedi, M., & Heydari, S. (2024). The efficacy of virtual reality for upper limb rehabilitation in stroke patients: A systematic review and meta-analysis. BMC Medical Informatics and Decision Making, 24, Article 135. https://doi.org/10.1186/s12911-024-02534-y
• Takeuchi, N., & Izumi, S.-I. (2013). Rehabilitation with poststroke motor recovery: A review with a focus on neural plasticity. Stroke Research and Treatment, 2013, Article 128641. https://doi.org/10.1155/2013/128641
• Tseng, K. C., Wang, L., Hsieh, C., & Wong, A. M. (2024). Portable robots for upper-limb rehabilitation after stroke: A systematic review and meta-analysis. Annals of Medicine, 56(1), Article 2337735. https://doi.org/10.1080/07853890.2024.2337735
• Veerbeek, J. M., Langbroek-Amersfoort, A. C., van Wegen, E. E. H., Meskers, C. G. M., & Kwakkel, G. (2017). Effects of robot-assisted therapy for the upper limb after stroke: A systematic review and meta-analysis. Neurorehabilitation and Neural Repair, 31(2), 107–121. https://doi.org/10.1177/1545968316666957
• Winstein, C. J., Stein, J., Arena, R., Bates, B., Cherney, L. R., Cramer, S. C., Deruyter, F., Eng, J. J., Fisher, B., Harvey, R. L., Lang, C. E., MacKay-Lyons, M., Ottenbacher, K. J., Pugh, S., Reeves, M. J., Richards, L. G., Stiers, W., & Zorowitz, R. D. (2016). Guidelines for adult stroke rehabilitation and recovery: A guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 47(6), e98–e169. https://doi.org/10.1161/STR.0000000000000098
• You, S. H., Jang, S. H., Kim, Y.-H., Hallett, M., Ahn, S. H., Kwon, Y.-H., & Lee, M. Y. (2005). Virtual reality-induced cortical reorganization and associated locomotor recovery in chronic stroke: An experimenter-blind randomized study. Stroke, 36(6), 1166–1171. https://doi.org/10.1161/01.STR.0000162715.43417.91
• Zhang, B., Wong, K. P., Kang, R., Fu, S., Qin, J., & Xiao, Q. (2023). Efficacy of robot-assisted and virtual reality interventions on balance, gait, and daily function in patients with stroke: A systematic review and network meta-analysis. Archives of Physical Medicine and Rehabilitation, 104(10), 1711–1719. https://doi.org/10.1016/j.apmr.2023.04.005
• Zhang, L., Jia, G., Ma, J., Wang, S., & Cheng, L. (2022). Short- and long-term effects of robot-assisted therapy on upper limb motor function and activity of daily living in patients post-stroke: A meta-analysis of randomized controlled trials. Journal of NeuroEngineering and Rehabilitation, 19, Article 76. https://doi.org/10.1186/s12984-022-01058-8
