Disability and Rehabilitation Assistive Technology

Intelligent assistive technologies in rehabilitation for older adults with Alzheimer's disease: systematic review and thematic analysis

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Abstract

PURPOSE: With population ageing, cognitive and functional impairments associated with Alzheimer's disease (AD) place demands on rehabilitation and long term care. Although intelligent assistive technologies (IATs), existing studies remain fragmented in terms of their development, application, and implementation. This study aimed to systematically review evidence on IAT applications in AD rehabilitation and developed, implemented, and evaluated. METHODS: A systematic review was conducted using a predefined search strategy four electronic databases (PubMed, Taylor & Francis Online, Scopus, and Web of Science). Two reviewers independently screened titles/abstracts and full texts according to predefined criteria, yielding 26 eligible studies. Methodological quality was assessed using the Mixed Methods Appraisal Tool (MMAT), and thematic analysis was used to synthesise the findings and extract key themes. RESULTS: The 26 included studies were generally rated as having moderate to high methodological quality. Most studies were small scale feasibility trials, with reported benefits mainly in user engagement and short term improvements. Evidence for sustained cognitive and functional improvement remains limited. Thematic analysis identified 4 core themes and 15 sub themes, covering technology modalities, intervention design and implementation, rehabilitation outcomes, and influencing factors. CONCLUSIONS: The proposed Intelligent Intervention Development (IID) framework integrates technology development, intervention design and implementation, rehabilitation outcomes, and influencing factors. Moving beyond feasibility studies, future research should address long term effectiveness, implementation strategies, and scalability in real world care settings.

The paper

Universiti Putra Malaysia

Disability and Rehabilitation Assistive Technology, 13 Oct 2026

doi.org/10.1080/17483107.2026.2735597PubMed 42867198