Gaming Technology for Pediatric Neurorehabilitation: A Systematic Review
Overview
Affiliations
Introduction: The emergence of gaming technologies, such as videogames and virtual reality, provides a wide variety of possibilities in intensively and enjoyably performing rehabilitation for children with neurological disorders. Solid evidence-based results are however required to promote the use of different gaming technologies in pediatric neurorehabilitation, while simultaneously exploring new related directions concerning neuro-monitoring and rehabilitation in familiar settings.
Aim Of The Study And Methods: In order to analyze the state of the art regarding the available gaming technologies for pediatric neurorehabilitation, Scopus and Pubmed Databases have been searched by following: PRISMA statements, PICOs classification, and PEDro scoring.
Results: 43 studies have been collected and classified as follows: 11 feasibility studies; six studies proposing home-system solutions; nine studies presenting gamified robotic devices; nine longitudinal intervention trials; and eight reviews. Most of them rely on feasibility or pilot trials characterized by small sample sizes and short durations; different methodologies, outcome assessments and terminologies are involved; the explored spectrum of neurological conditions turns out to be scanty, mainly including the most common and wider debilitating groups of conditions in pediatric neurology: cerebral palsy, brain injuries and autism.
Conclusion: Even though it highlights reduced possibilities of drawing evidence-based conclusions due to the above outlined biases, this systematic review raises awareness among pediatricians and other health professionals about gaming technologies. Such a review also points out a definite need of rigorous studies that clearly refer to the underlying neuroscientific principles.
Sokolowska E, Sokolowska B, Chrapusta S, Sulejczak D Front Neurosci. 2025; 18:1461142.
PMID: 39886337 PMC: 11780595. DOI: 10.3389/fnins.2024.1461142.
Consales A, Biffi E, Nossa R, Pittaccio S, Lazzari F, Malosio M Ital J Pediatr. 2024; 50(1):263.
PMID: 39707421 PMC: 11662457. DOI: 10.1186/s13052-024-01830-7.
Machine learning enables update to pediatric neurorehabilitation.
He Y, Cai S, Peng T, Qiao Y, Wu N, Xu K Pediatr Investig. 2024; 8(3):237-239.
PMID: 39347526 PMC: 11427893. DOI: 10.1002/ped4.12418.
Gatica-Rojas V, Cartes-Velasquez R Int J Environ Res Public Health. 2023; 20(18).
PMID: 37754586 PMC: 10531484. DOI: 10.3390/ijerph20186726.
Identifying Soccer Players' Playing Styles: A Systematic Review.
Plakias S, Moustakidis S, Kokkotis C, Papalexi M, Tsatalas T, Giakas G J Funct Morphol Kinesiol. 2023; 8(3).
PMID: 37606399 PMC: 10443261. DOI: 10.3390/jfmk8030104.