ArticleBioengineering (Basel, Switzerland)2025
Towards Clinical Trial Readiness: Optimization of a Parallel Robot for Lower Limb Rehabilitation.
Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
This study presents the clinical trial readiness and optimization of a parallel robotic system developed for early-stage lower limb rehabilitation of bedridden patients using feedback from healthy users and clinicians. The system combines a parallel hip-knee mechanism with a Bowden cable-driven ankle module, both actuated by servomotors and controlled through a PLC platform. Experimental tests were performed in laboratory conditions with twenty healthy participants (aged 25-45) and ten clinicians, focusing on safety, ergonomics, clinical usability, and comfort through structured questionnaires. The responses were quantified and analyzed using a Mamdani-type fuzzy logic model, allowing subjective feedback to be converted into objective redesign priorities. Safety, torque capacity, and adaptability emerged as the key areas that need improvement. Subsequent mechanical and structural refinements resulted in substantial gains in user comfort, perceived safety, and clinician-reported applicability. The optimized robotic system demonstrates enhanced functionality and improved readiness for clinical evaluation, highlighting the benefit of incorporating fuzzy logic-based feedback into the development of rehabilitation robots.
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Registered trials
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