Technological frontiers in neuropsychological rehabilitation: a bibliometric-systematic literature review of AI applications for pediatric, adult, and geriatric populations

The integration of artificial intelligence (AI) into neuropsychological rehabilitation represents an expanding technological frontier, yet no study has systematically mapped this field across the lifespan. This bibliometric-systematic review analyzed 4336 Scopus-indexed publications (2020–2025) across pediatric ( n = 366), adult ( n = 883), and geriatric ( n = 3,087) populations using Bibliometrix. Results reveal an overwhelming disparity: research on older adults exceeds that on children and adults by eightfold. Geriatric research shows sustained annual growth (≈ 18.5 articles/year), while pediatric and adult corpora exhibit volatile, non-linear patterns (R²=0.0515 and 0.0087), indicating lack of research consolidation. Virtual reality emerged as the central cross-cutting technology, yet with marked specialization: in pediatrics, associated with executive functions training; in older adults, combined with machine learning for cognitive assessment (highest impact: 4.250). Thematic foci align with epidemiological priorities—neurodevelopmental disorders in children, acquired conditions in adults, neurodegenerative diseases in older adults—while revealing methodological stratification: geriatric research integrates neuroimaging with AI; pediatric research emphasizes behavioral interventions. High-impact niches identified include AI-integrated neurofeedback in pediatrics (impact 2.052) and VR with machine learning for mild cognitive impairment in gerontology (impact 4.250). Working-age adults with acquired brain injuries emerge as a persistently underserved population. This first comparative cartography of AI-enabled neuropsychological rehabilitation across the lifespan offers actionable insights for strategic resource allocation and identifies critical gaps requiring urgent attention.