Human-AI collaboration for dysphagia rehabilitation from effectiveness to implementation complexity: a systematic review.

Abstract

Oropharyngeal dysphagia affects over half of neurological and oncological populations, yet rehabilitation is constrained by a global therapist shortage that human-AI collaboration has not demonstrably addressed. Here we report a systematic review of 31 studies (1012 participants; PROSPERO: CRD420251115997) evaluating AI-augmented swallowing rehabilitation in adults with oropharyngeal dysphagia, or in healthy volunteers testing systems designed for clinical application. We synthesised findings by aetiology and collaboration mode, assessing risk of bias and certainty of evidence (Grading of Recommendations, Assessment, Development and Evaluation, GRADE). AI-augmented interventions produce short-term gains in functional oral intake and physiological measures (GRADE moderate/low certainty), but these effects attenuate within weeks of cessation, and adherence declines sharply once clinician supervision is withdrawn. NASSS framework analysis reveals a central paradox: the adopter domain-digital literacy, cognitive impairment, interface usability-is the dominant implementation barrier (61.3% rated high), meaning the populations with the greatest need face the steepest barriers to adoption. AI algorithm performance is rated at very low certainty, with validation largely confined to healthy volunteers. These findings support advancement to pragmatic trials for supervised post-stroke rehabilitation but underscore that evidence for other aetiologies, unsupervised settings, and sustained outcomes remains insufficient.