AI-driven cognitive telerehabilitation for stroke: a randomized controlled trial

Background Cognitive impairment is a common consequence of stroke, requiring effective rehabilitation strategies. Telerehabilitation has emerged as a promising alternative to in-person cognitive therapy, yet existing systems often lack mechanisms for real-time personalization and engagement monitoring. This study aimed to evaluate the clinical effectiveness of a self-guided AI-driven cognitive telerehabilitation compared to a therapist-supervised rehabilitation in subacute stroke patients. Methods In this multicenter, parallel-group, randomized controlled non-inferiority trial, 63 participants with cognitive impairment within 6 months of stroke onset were randomized 1:1 to either a self-guided AI-driven telerehabilitation group or a therapist-supervised rehabilitation group. Both groups completed 24 sessions within 6 weeks using the same mobile platform. The primary outcomes were cognitive function measures, including the Korean Mini-Mental State Examination-2 (K-MMSE2), Trail Making Tests (A and B), and Digit Span Tests (forward and backward), with non-inferiority formally tested using the K-MMSE2. Secondary outcomes included functional independence, psychosocial measures and usability questionnaire. Results Fifty-five participants completed the study. Both groups showed significant improvements across all primary cognitive measures, with no statistically significant differences between groups. Non-inferiority analysis confirmed that the self-guided AI-driven telerehabilitation was not inferior to the therapist-supervised rehabilitation based on K-MMSE2 changes. Usability assessment among users of the cognitive rehabilitation system indicated high overall satisfaction with no serious adverse events reported. Conclusion This study demonstrates that a self-guided AI-driven telerehabilitation can deliver cognitive improvements comparable to a therapist-supervised rehabilitation in subacute stroke patients. Clinical trial registration https://cris.nih.go.kr/cris/index/index.do , KCT0008969.

Abstract licence: CC BY

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