ArticleJournal of prosthetics and orthotics : JPO2022
Robotic Emulation of Candidate Prosthetic Foot Designs May Enable Efficient, Evidence-Based, and Individualized Prescriptions.
Article in Journal of prosthetics and orthotics : JPO, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Toward personalizing prosthesis prescription: A take-home study of three microprocessor-controlled prosthetic knees: A randomized crossover study.PM & R : the journal of injury, function, and rehabilitation · 2026Trial
- Trial
- Robot-assisted Computer-Implant surgery : A comprehensive review of system architecture, clinical accuracy, and emerging technologies.Journal of robotic surgery · 2026Review
- User preference in the personalized control of an ankle prosthesis: a case study.Journal of neuroengineering and rehabilitation · 2026Article
- Future Directions in Prosthetic Component Research and Clinical Prescription: A Precision Rehabilitation and Patient-Centered Care Approach.Archives of physical medicine and rehabilitation · 2024Article
- Review
- Variable-stiffness prosthesis improves biomechanics of walking across speeds compared to a passive device.Scientific reports · 2024Article
- A patient-centered 'test-drive' strategy for ankle-foot orthosis prescription: Protocol for a randomized participant-blinded trial.PloS one · 2024Article
- Design, Control, and Evaluation of a Robotic Ankle-Foot Prosthesis Emulator.IEEE transactions on medical robotics and bionics · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Introduction: The design and selection of lower-limb prosthetic devices is currently hampered by a shortage of evidence to drive the choice of prosthetic foot parameters. We propose a new approach wherein prostheses could be designed, specified, and provided based on individualized measurements of the benefits provided by candidate feet. In this manuscript, we present a pilot test of this evidence-based and personalized process. Methods: We previously developed a "prosthetic foot emulator," a wearable robotic system that provides users with the physical sensation of trying on different prosthetic feet before definitive fitting. Here we detail preliminary demonstrations of two possible approaches to personalizing foot design: 1) an emulation and test-drive strategy of representative commercial foot models, and 2) a prosthetist-driven tuning procedure to optimize foot parameters. Results: The first experiment demonstrated large and sometimes surprising differences in optimal prosthetic foot parameters across a variety of subjects, walking conditions, and outcome measures. The second experiment demonstrated a quick and effective simple manual tuning procedure for identifying preferred prosthetic foot parameters. Conclusions: Emulator-based approaches could improve individualization of prosthetic foot prescription. The present results motivate future clinical studies of the validity, efficacy, and economics of the approach across larger and more diverse subject populations. Clinical Relevance: Today, emulator technology is being used to accelerate research and development of novel prosthetic and orthotic devices. In the future, after further refinement and validation, this technology could benefit clinical practice by providing a means for rapid test-driving and optimal selection of clinically available prosthetic feet.
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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 Socratic graph.