ArticleFrontiers in public health2023
Co-designing an interactive artificial intelligent system with post-stroke patients and caregivers to augment the lost abilities and improve their quality of life: a human-centric approach.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Building trust in long-term care settings using assistive technology: a systematic review.Frontiers in rehabilitation sciences · 2024Pooled it
- User Needs for an Artificial Intelligence-Empowered Basic Activities of Daily Living Training System After Stroke: A Qualitative Study.Journal of multidisciplinary healthcare · 2026Article
- Framing the Human-Centered Artificial Intelligence Concepts and Methods: Scoping Review.JMIR human factors · 2025Article
- Integrating AI and Assistive Technologies in Healthcare: Insights from a Narrative Review of Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review.Frontiers in cardiovascular medicine · 2025Review
- Exploring the dynamics of stroke survivors' care dependency, fatigue, and coping strategy in their caregivers: a structural equation modeling analysis.Frontiers in public health · 2025Article
- AI technology to support adaptive functioning in neurodevelopmental conditions in everyday environments: a systematic review.NPJ digital medicine · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: The motor disability due to stroke compromises the autonomy of patients and caregivers. To support autonomy and other personal and social needs, trustworthy, multifunctional, adaptive, and interactive assistive devices represent optimal solutions. To fulfill this aim, an artificial intelligence system named MAIA would aim to interpret users' intentions and translate them into actions performed by assistive devices. Analyzing their perspectives is essential to develop the MAIA system operating in harmony with patients' and caregivers' needs as much as possible. Methods: Post-stroke patients and caregivers were interviewed to explore the impact of motor disability on their lives, previous experiences with assistive technologies, opinions, and attitudes about MAIA and their needs. Interview transcripts were analyzed using inductive thematic analysis. Results: Sixteen interviews were conducted with 12 post-stroke patients and four caregivers. Three themes emerged: (1) Needs to be satisfied, (2) MAIA technology acceptance, and (3) Perceived trustfulness. Overall, patients are seeking rehabilitative technology, contrary to caregivers needing assistive technology to help them daily. An easy-to-use and ergonomic technology is preferable. However, a few participants trust a system based on artificial intelligence. Conclusion: An interactive artificial intelligence technology could help post-stroke patients and their caregivers to restore motor autonomy. The insights from participants to develop the system depends on their motor ability and the role of patients or caregiver. Although technology grows exponentially, more efforts are needed to strengthen people's trust in advanced technology.
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