ReviewJournal of neuroengineering and rehabilitation2025
Automated planning and scheduling in robot-aided rehabilitation: a review.
Review in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
3 authors.
Funding
Abstract
Robotic systems are increasingly utilized in rehabilitation contexts, offering tailored support for physical and cognitive functions. Enabling these systems to autonomously personalize treatments entails a critical role for automated planning and scheduling methodologies. However, a comprehensive review to map the control architectures of robotic rehabilitation systems that leverage automated planning for long-term customization is lacking, addressing a key gap in the literature. To bridge such a gap, this review systematically analyzed 26 studies retrieved from scientific databases after a careful selection performed following PRISMA guidelines. The search focused on works employing automated planning in robot-aided rehabilitation across physical and cognitive domains, as well as multi-user robotic environments. Papers were selected based on predefined criteria, including relevance to automated planning, peer-reviewed publication, and a focus on robotic systems in rehabilitation. The discussion highlights the primary similarities and differences in control architectures, adaptation strategies, and validation approaches among the reviewed systems. This review emphasizes the potential of automated planning to enhance personalization and adaptability in robotic rehabilitation, offering a foundation for more efficient and patient-centered therapeutic solutions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.