Use of neurotechnologies in the rehabilitation of patients with brain damage or stroke

Eloisa Gabriela Zuñiga Valencia
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Eloisa Gabriela Zuñiga Valencia: Universidad Catolica De Santa Maria. Perú

NeuroData, 2026, vol. 3, 161

Abstract: Introduction: Acquired brain damage and stroke are relevant causes of neurological disability, generating motor, cognitive and functional alterations that affect the autonomy and quality of life of patients. In this context, neurotechnologies have emerged as innovative tools to strengthen neurological rehabilitation processes, through applications such as therapeutic virtual reality, brain-computer interfaces, non-invasive brain stimulation and neurofeedback.Methodology: A review of scientific literature was carried out in specialized academic databases, including PubMed, Scopus, Web of Science and Google Scholar. We considered studies published mainly between 2015 and 2026, related to the application of neurotechnologies in the rehabilitation of patients with acquired brain damage and stroke. The selection was made using inclusion and exclusion criteria aimed at guaranteeing the thematic relevance and scientific quality of the sources.Results: The reviewed evidence shows that neurotechnologies contribute to improving functional recovery, especially in mobility, motor coordination, cognitive stimulation and therapeutic participation. Virtual reality stands out for promoting motivation and motor learning, while brain-computer interfaces, non-invasive brain stimulation and neurofeedback expand the possibilities of personalized clinical intervention.Conclusions: Neurotechnologies represent a promising strategy in neurorehabilitation, although their implementation still faces challenges related to accessibility, costs, infrastructure and professional training. More robust clinical studies are needed to consolidate its efficacy and facilitate its integration into health systems.

Keywords: neurotechnologies; neurological rehabilitation; brain damage; neurofeedback; neuroplasticity (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cxn:neurod:v:3:y:2026:id:161

DOI: 10.63688/neurodata2026161

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