Artificial intelligence in upper-limb, language and cognitive neurorehabilitation after stroke

PURPOSE OF REVIEW: Artificial intelligence (AI) is being increasingly integrated into upper-limb, language and cognitive neurorehabilitation research and there is interest in where the research currently lies along the pipeline towards clinical implementation and real-world impact. RECENT FINDINGS: Across these three domains of neurorehabilitation, the research into the use of AI has shown clear potential to enhance assessment, personalize rehabilitation and extend access to care but is yet to demonstrate clinical utility and superiority over other digital rehabilitation approaches. There remain concerns about small and selective datasets being used for modelling, privacy and equity issues and sustainable implementation. It is suggested that AI should be positioned as an important tool in the clinical infrastructure rather than an autonomous clinical decision maker within clinical practice. SUMMARY: Future research across these neurorehabilitation domains should consider implementation risks and needs early in the research pipeline, by using ethical principles and guidelines to ensure transparency and consumer involvement in AI research and implementation into clinical practice.

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Publication Details

Journal
Current Opinion in Neurology
Published
2026-10-26
DOI
https://doi.org/10.1097/wco.0000000000001530
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
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article

Artificial intelligence in upper-limb, language and cognitive neurorehabilitation after stroke

Carl Froilan D. Leochico, Christoph Michael Bauer, Annie Hill
Current Opinion in Neurology
Stroke Rehabilitation and Recovery
article

Artificial intelligence in upper-limb, language and cognitive neurorehabilitation after stroke

Carl Froilan D. Leochico, Christoph Michael Bauer, Annie Hill
article en

Abstract

PURPOSE OF REVIEW: Artificial intelligence (AI) is being increasingly integrated into upper-limb, language and cognitive neurorehabilitation research and there is interest in where the research currently lies along the pipeline towards clinical implementation and real-world impact. RECENT FINDINGS: Across these three domains of neurorehabilitation, the research into the use of AI has shown clear potential to enhance assessment, personalize rehabilitation and extend access to care but is yet to demonstrate clinical utility and superiority over other digital rehabilitation approaches. There remain concerns about small and selective datasets being used for modelling, privacy and equity issues and sustainable implementation. It is suggested that AI should be positioned as an important tool in the clinical infrastructure rather than an autonomous clinical decision maker within clinical practice. SUMMARY: Future research across these neurorehabilitation domains should consider implementation risks and needs early in the research pipeline, by using ethical principles and guidelines to ensure transparency and consumer involvement in AI research and implementation into clinical practice.

Current Opinion in Neurology
University Health Network (CA), University of Lucerne (CH), The University of Queensland (AU), University of Toronto (CA), La Trobe University (AU), University of Zurich (CH), Toronto Rehabilitation Institute (CA), Philippine General Hospital (PH), St. Luke's Medical Center (PH), University of the Philippines Manila (PH), University of Jyväskylä (FI)
Openalex Percentile: Top 16%
Stroke Rehabilitation and Recovery
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Artificial intelligence in upper-limb, language and cognitive neurorehabilitation after stroke — Carl Froilan D. Leochico, Christoph Michael Bauer, et al. · Current Opinion in Neurology (2026) | TGRS Research Map | TGRS