Objective
To test the feasibility and usability of an artificial intelligence (AI)-guided mobile cognitive telerehabilitation program for patients with stroke or older adults with mild cognitive impairment (MCI).
Methods
Thirteen participants with cognitive impairment (Mini-Mental State Examination [MMSE] score≤26; nine with stroke and four with MCI) were enrolled in the study. Each participant was provided with an AI-guided mobile cognitive rehabilitation program (Zenicog®). Participants were instructed to complete 24 sessions within 6 weeks, and those with sufficient adherence (≥70%, 17 sessions) were included in the analysis. Cognitive assessments included the MMSE, digit span, and Trail Making Tests A & B. The usability questionnaire investigated equitable use and flexibility in use, simple and intuitive use, perceptible information, tolerance for error, low physical effort, size and space for use, overall product quality, overall satisfaction.
Results
Eleven participants completed the study, and 10 participants met adherence criteria. The MMSE score increased significantly from 24.00 [21.00, 25.75] at baseline to 27.50 [26.00, 28.75] after intervention. The overall product quality (Likert scale: 1–5) score was 4.00±0.87. The lowest score in the usability questionnaire was for tolerance for error. Female participants and participants with <12 years’ education gave lower scores for tolerance for error and equitable/ flexibility in use, respectively.
Conclusion
The AI-guided mobile cognitive telerehabilitation program is feasible and potentially beneficial for improving cognitive function in patients with stroke or older adults with MCI. Individuals who are less familiar with electronic devices require special consideration to improve their usability.

Citations

• AI-driven telerehabilitation for older adults with mild cognitive impairment: a randomized controlled trial
  Minsong Kim, Doo Young Kim, Taeksoo Jeong, Si-Woon Park
  Frontiers in Neurology.2026;[Epub]     CrossRef