{"title":"Effectiveness of AI-Assisted Digital Therapies for Post-Stroke Aphasia Rehabilitation: A Systematic Review.","authors":"Yamil Liscano, Lina Marcela Bernal, Jhony Alejandro Díaz Vallejo","doi":"10.3390/brainsci15091007","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Traditional aphasia therapy is often limited by insufficient dosage, a barrier that AI-assisted digital therapies are poised to overcome. However, it remains unclear whether gains on specific tasks translate to functional, real-world communication. This systematic review evaluates the effectiveness of these novel interventions and investigates the potential for a \"generalization gap\" when compared to conventional treatments for post-stroke aphasia rehabilitation. <b>Methods:</b> Following PRISMA guidelines, we systematically reviewed randomized controlled trials (2010-2024) from six databases. We included studies examining AI-powered digital platforms for adults with chronic post-stroke apha-sia that reported standardized language outcomes. <b>Results:</b> Our analysis of five trials (<i>n</i> = 366) shows that AI-assisted therapies successfully deliver high-dose interventions, leading to significant improvements in trained language skills, including word retrieval (up to 16.4% gain) and auditory comprehension. However, a critical \"generalization gap\" was consistently identified: these impairment-level gains rarely transferred to functional, real-world communication. <b>Conclusions:</b> AI-assisted digital therapies effectively solve the dosage problem in aphasia care and improve specific linguistic deficits. Their primary limitation is the failure to generalize skills to everyday use. Future platforms must therefore be strategically redesigned to incorporate therapeutic principles that explicitly target the transfer of skills, bridging the gap between clinical improvement and functional communication.</p>","PeriodicalId":9095,"journal":{"name":"Brain Sciences","volume":"15 9","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468904/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/brainsci15091007","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Traditional aphasia therapy is often limited by insufficient dosage, a barrier that AI-assisted digital therapies are poised to overcome. However, it remains unclear whether gains on specific tasks translate to functional, real-world communication. This systematic review evaluates the effectiveness of these novel interventions and investigates the potential for a "generalization gap" when compared to conventional treatments for post-stroke aphasia rehabilitation. Methods: Following PRISMA guidelines, we systematically reviewed randomized controlled trials (2010-2024) from six databases. We included studies examining AI-powered digital platforms for adults with chronic post-stroke apha-sia that reported standardized language outcomes. Results: Our analysis of five trials (n = 366) shows that AI-assisted therapies successfully deliver high-dose interventions, leading to significant improvements in trained language skills, including word retrieval (up to 16.4% gain) and auditory comprehension. However, a critical "generalization gap" was consistently identified: these impairment-level gains rarely transferred to functional, real-world communication. Conclusions: AI-assisted digital therapies effectively solve the dosage problem in aphasia care and improve specific linguistic deficits. Their primary limitation is the failure to generalize skills to everyday use. Future platforms must therefore be strategically redesigned to incorporate therapeutic principles that explicitly target the transfer of skills, bridging the gap between clinical improvement and functional communication.
期刊介绍:
Brain Sciences (ISSN 2076-3425) is a peer-reviewed scientific journal that publishes original articles, critical reviews, research notes and short communications in the areas of cognitive neuroscience, developmental neuroscience, molecular and cellular neuroscience, neural engineering, neuroimaging, neurolinguistics, neuropathy, systems neuroscience, and theoretical and computational neuroscience. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.