ReviewExpert review of medical devices2016
A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke.
Review in Expert review of medical devices, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
54 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Efficacy of Brain-Computer Interface Therapy for Upper Limb Rehabilitation in Chronic Stroke: Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- Influence of age, cognitive function, attention, and mental state on the effectiveness of EEG-based brain-computer interface device use: a systematic review.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022Pooled it
- Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain-Computer Interfaces: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Multimodal assessment of a BCI system for stroke rehabilitation integrating motor imagery and motor attempts: a randomized controlled trial.Journal of neuroengineering and rehabilitation · 2025Trial
- Brain computer interface training with motor imagery and functional electrical stimulation for patients with severe upper limb paresis after stroke: a randomized controlled pilot trial.Journal of neuroengineering and rehabilitation · 2024Trial
- Trial
- Effects of Brain-Computer Interface-Controlled Hand Robot Training on Post-Stroke Recovery of Upper Limb Motor Functions: A Meta-Analysis of Dose-Matched Randomized Controlled Trials.Brain sciences · 2026Review
- Corticomuscular coherence and its non-invasive modulation in stroke applications: a narrative review.Neuroimage. Reports · 2026Article
- Brain-computer interface technology for motor rehabilitation in severe stroke: a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Deep Learning Discrimination for BCI Implementation Using 3D Convolutional Neural Network and EEG Topographic Maps.Advances in experimental medicine and biology · 2026Article
- Synergistic effects of action observation and object affordance on cortical excitability during BCI-triggered motor imagery in stroke: a randomized, within-subject, 2 × 2 factorial study protocol.Frontiers in human neuroscience · 2026Article
- Hebbian plasticity induced by temporally coincident BCI enhances post-stroke motor recovery.Scientific reports · 2024Article
- Article
- New approaches to recovery after stroke.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Review
- Electroencephalogram-based adaptive closed-loop brain-computer interface in neurorehabilitation: a review.Frontiers in computational neuroscience · 2024Review
- Stroke rehabilitation: from diagnosis to therapy.Frontiers in neurology · 2024Review
- Correlation between the ERD in grasp/open tasks of BCIs and hand function of stroke patients: a cross-sectional study.Biomedical engineering online · 2023Article
- Identifying Thematics in a Brain-Computer Interface Research.Computational intelligence and neuroscience · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Stroke is a leading cause of acquired disability resulting in distal upper extremity functional motor impairment. Stroke mortality rates continue to decline with advances in healthcare and medical technology. This has led to an increased demand for advanced, personalized rehabilitation. Survivors often experience some level of spontaneous recovery shortly after their stroke event, yet reach a functional plateau after which there is exiguous motor recovery. Nevertheless, studies have demonstrated the potential for recovery beyond this plateau. Non-traditional neurorehabilitation techniques, such as those incorporating the brain-computer interface (BCI), are being investigated for rehabilitation. BCIs may offer a gateway to the brain's plasticity and revolutionize how humans interact with the world. Non-invasive BCIs work by closing the proprioceptive feedback loop with real-time, multi-sensory feedback allowing for volitional modulation of brain signals to assist hand function. BCI technology potentially promotes neuroplasticity and Hebbian-based motor recovery by rewarding cortical activity associated with sensory-motor rhythms through use with a variety of self-guided and assistive modalities.
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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.