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Published on: February 16, 2011
Innovative Assistive Technologies for Tetraplegia: A Narrative Review of Systematic and Emerging Evidence
Lorenzo Desideri1, Regina Gregori Grgič1, Antonia Pirrera2
1Digital Psychology Lab, Sigmund Freud University, 20143 Milano, Italy.
None:
Background: Assistive technologies (ATs) for individuals with tetraplegia have evolved from mechanical aids to complex neurotechnological, digital, and psychosocial systems. However, the evidence base remains fragmented, with heterogeneous methodologies and limited integration across domains. This review synthesizes recent review-level evidence to clarify current trends, gaps, and directions in ATs for tetraplegia. Methods: A narrative review of reviews was conducted following the ANDJ checklist. PubMed and Scopus were searched for systematic, scoping, and narrative reviews addressing assistive technologies relevant to tetraplegia. After screening, de-duplication, and quality appraisal, 20 reviews were included and synthesized narratively. Results: The included reviews clustered into four main domains: neural and regenerative interfaces, motor and biomechanical assistive systems, digital and adaptive rehabilitation ecosystems, and psychosocial and integrative frameworks. Across domains, evidence highlights a shift toward personalized, adaptive, and interoperable systems, supported by neurotechnologies, robotics, mobile health, and virtual reality. Common limitations include heterogeneous outcome measures, scarcity of longitudinal evidence, limited system interoperability, and persistent inequities in access and adoption. Emerging applications of artificial intelligence support adaptive control, monitoring, and personalization, though robust clinical validation remains limited. Conclusions: This synthesis provides a structured overview of review-level evidence on assistive technologies for tetraplegia. The findings underscore the need for coordinated, multidisciplinary approaches and more rigorous, longitudinal evaluation to support the development of inclusive, human-centered, and interoperable assistive ecosystems.
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