Trial reportNeuroRehabilitation2018
Error-augmented bimanual therapy for stroke survivors.
Trial report in NeuroRehabilitation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- On the correlation between training modalities and recovery stages in poststroke robotic rehabilitation of the upper limb: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Does visual error augmentation offer advantages during bimanual therapy in individuals poststroke? A randomized controlled trial.The Journal of international medical research · 2025Trial
- Error fields: personalized robotic movement training that augments one's more likely mistakes.Scientific reports · 2025Trial
- Evaluating self-assistance during functional reach with a passive hydrostatic exoskeleton under artificial impairment.Journal of neuroengineering and rehabilitation · 2025Article
- Post-Stroke Rehabilitation: Neurophysiology Processes of Bilateral Movement Training and Interlimb Coupling-A Systematic Review.Journal of clinical medicine · 2025Review
- MovementVR: An open-source tool for the study of motor control and learning in virtual reality.ArXiv · 2025Article
- Error Enhancement for Upper Limb Rehabilitation in the Chronic Phase after Stroke: A 5-Day Pre-Post Intervention Study.Sensors (Basel, Switzerland) · 2024Article
- Bimanual motor skill learning and robotic assistance for chronic hemiparetic stroke: a randomized controlled trial.Neural regeneration research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundStroke recovery studies have shown the efficacy of bimanual training on upper limb functional recovery and others have shown the efficacy of feedback technology that augments error.
objectiveIn a double-blinded randomized controlled study (N = 26), we evaluated the short-term effects of bilateral arm training to foster functional recovery of a hemiparetic arm, with half of our subjects unknowingly also receiving error augmentation (where errors were visually and haptically enhanced by a robot).
methodsTwenty-six individuals with chronic stroke were randomly assigned to practice an equivalent amount of bimanual reaching either with or without error augmentation. Participants were instructed to coordinate both arms while reaching to two targets (one for each arm) in three 45-minute treatments per week for two weeks, with a follow-up visit after one week without treatment.
resultsSubjects' 2-week gains in Fugl-Meyer score averaged 2.92, and we also observed improvements Wolf Motor Functional Ability Scale average 0.21, and Motor Activity Log of 0.58 for quantity and 0.63 for quality of life scores. The extra benefit of error augmentation over the three weeks became apparent in Fugl-Meyer score only after removing an outlier from consideration.
conclusionsThis modest advantage of error augmentation was detectable over a short interval encouraging further research in interactive self-rehabilitation systems that can enhance error motor recovery.
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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.