ArticleNeurorehabilitation and neural repair2019
A Single Session of Robot-Controlled Proprioceptive Training Modulates Functional Connectivity of Sensory Motor Networks and Improves Reaching Accuracy in Chronic Stroke.
Article in Neurorehabilitation and neural repair, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses 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
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.
- Robot-Assisted Upper-Limb Rehabilitation After Stroke: A Systematic Review and Meta-Analysis of Cortical Reorganization and Neuroplasticity Biomarkers.Neural plasticity · 2026Pooled it
- Interventions for perceptual disorders following stroke.The Cochrane database of systematic reviews · 2022Pooled it
- The impact of bimanual reach training with augmented position sense feedback on post-stroke upper limb somatosensory and motor impairment.Journal of neuroengineering and rehabilitation · 2025Trial
- Variants of active assist robotic therapy: feasibility of virtual assistance and proprioceptive training as gauged by their effects on success and motivation during finger movement training after stroke.Journal of neuroengineering and rehabilitation · 2025Trial
- The effect of mirror therapy can be improved by simultaneous robotic assistance.Restorative neurology and neuroscience · 2022Trial
- Proprioceptive Training with Visual Feedback Improves Upper Limb Function in Stroke Patients: A Pilot Study.Neural plasticity · 2022Trial
- Effects of a robot-aided somatosensory training on proprioception and motor function in stroke survivors.Journal of neuroengineering and rehabilitation · 2021Trial
- Network-oriented neurorehabilitation after stroke: a paradigmatic approach.Journal of neuroengineering and rehabilitation · 2026Review
- Expansion of attentional scope modulates postural control, motor strategies, and attentional network connectivity in healthy adults: a proof-of-concept mixed-methods study.Frontiers in rehabilitation sciences · 2026Article
- A structural causal model for robot-assisted upper-limb neurorehabilitation.Frontiers in rehabilitation sciences · 2026Article
- A pilot study for self-guided, active robotic training of proprioception of the upper limb in chronic stroke.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
- Article
- Relearning Upper Limb Proprioception After Stroke Through Robotic Therapy: A Feasibility Analysis.Journal of clinical medicine · 2025Article
- The Role of Sensory Impairments on Recovery and Rehabilitation After Stroke.Current neurology and neuroscience reports · 2025Review
- AI Applications in Adult Stroke Recovery and Rehabilitation: A Scoping Review Using AI.Sensors (Basel, Switzerland) · 2024Article
- The Consolidation of Newly Learned Movements Depends upon the Somatosensory Cortex in Humans.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Resting state functional connectivity associated with impaired proprioception post-stroke.Human brain mapping · 2024Article
- Characteristics and Emerging Trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study.Journal of medical Internet research · 2023Article
- Predicting poststroke dyskinesia with resting-state functional connectivity in the motor network.Neurophotonics · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundPassive robot-generated arm movements in conjunction with proprioceptive decision making and feedback modulate functional connectivity (FC) in sensory motor networks and improve sensorimotor adaptation in normal individuals. This proof-of-principle study investigates whether these effects can be observed in stroke patients.
methodsA total of 10 chronic stroke patients with a range of stable motor and sensory deficits (Fugl-Meyer Arm score [FMA] 0-65, Nottingham Sensory Assessment [NSA] 10-40) underwent resting-state functional magnetic resonance imaging before and after a single session of robot-controlled proprioceptive training with feedback. Changes in FC were identified in each patient using independent component analysis as well as a seed region-based approach. FC changes were related to impairment and changes in task performance were assessed.
resultsA single training session improved average arm reaching accuracy in 6 and proprioception in 8 patients. Two networks showing training-associated FC change were identified. Network C1 was present in all patients and network C2 only in patients with FM scores >7. Relatively larger C1 volume in the ipsilesional hemisphere was associated with less impairment ( r = 0.83 for NSA, r = 0.73 for FMA). This association was driven by specific regions in the contralesional hemisphere and their functional connections (supramarginal gyrus with FM scores r = 0.82, S1 with NSA scores r = 0.70, and cerebellum with NSA score r = -0.82).
conclusionA single session of robot-controlled proprioceptive training with feedback improved movement accuracy and induced FC changes in sensory motor networks of chronic stroke patients. FC changes are related to functional impairment and comprise bilateral sensory and motor network nodes.
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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.