ReviewNeurorehabilitation and neural repair2022
Brain-Computer Interface-Controlled Exoskeletons in Clinical Neurorehabilitation: Ready or Not?
Review in Neurorehabilitation and neural repair, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07553416 (A Prospective, Randomized, Parallel-Controlled Clinical Study Protocol of Non-Invasive Brain Computer Interface Robot Based on Mirror Rehabilitation Theory in the Treatment of Upper Limb Motor Function Disorder After Stroke), which is not on this map. Cited by 33 papers, 3 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.
A Prospective, Randomized, Parallel-Controlled Clinical Study Protocol of Non-Invasive Brain Computer Interface Robot Based on Mirror Rehabilitation Theory in the Treatment of Upper Limb Motor Function Disorder After Stroke
Who cites it
33 citing papers in PubMed, 3 syntheses or guidelines pooled it, 83 citations in OpenAlex.
- Comparison of the effects of transcranial direct current stimulation combined with different rehabilitation interventions on motor function in people suffering from stroke-related symptoms: a systematic review and network meta-analysis.Frontiers in neurology · 2025Pooled it
- Global research trends and hotspots of artificial intelligence research in spinal cord neural injury and restoration-a bibliometrics and visualization analysis.Frontiers in neurology · 2024Pooled it
- Tracing the evolving dynamics and research hotspots of spinal cord injury and surgical decompression from 1975 to 2024: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- The Berlin bimanual test for stroke survivors (BeBiT-S): evaluating exoskeleton-assisted bimanual motor function after stroke.Journal of neuroengineering and rehabilitation · 2025Trial
- Effects of visually induced motor imagery-based brain-computer interface training on motor function in patients with incomplete spinal cord injury: a small-sample exploratory trial.Frontiers in neurologyTrial
- Neurorehabilitation in the 21st Century: New Science, New Strategies, New Expectations.Neurorehabilitation and neural repair · 2026Review
- Motor Imagery Brain-Computer Interface (MI-BCI)-Assisted Upper Limb Neurorehabilitation for Acute Stroke During Inpatient Rehabilitation: A Prospective Feasibility Study with Economic Evaluation Protocol.Journal of clinical medicine · 2026Article
- Robotic Rehabilitation in Spinal Cord Injury: Neurophysiological Basis and Severity-Based Clinical Framework.Brain sciences · 2026Review
- 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
- Innovative Assistive Technologies for Tetraplegia: A Narrative Review of Systematic and Emerging Evidence.Healthcare (Basel, Switzerland) · 2026Review
- Bridging cognition and control through passive eye movement integration in motor imagery brain-computer interfaces.Frontiers in human neuroscience · 2026Review
- Closed-loop brain-computer interfaces for post-stroke sensorimotor loop restoration.Frontiers in neuroscience · 2026Review
- Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026Review
- Characterization of error-related potentials during the command of a lower-limb exoskeleton based on deep learning.Journal of neuroengineering and rehabilitation · 2025Article
- A Novel Transfer Learning-Based Hybrid EEG-fNIRS Brain-Computer Interface for Intracerebral Hemorrhage Rehabilitation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- TMS-Based Neurofeedback Training of Mental Finger Individuation Induces Neuroplastic Changes in the Sensorimotor System.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Brain-Computer Interfaces for Stroke Motor Rehabilitation.Bioengineering (Basel, Switzerland) · 2025Review
- Master classes of the tenth international brain-computer interface meeting: showcasing the research of BCI trainees.Journal of neural engineering · 2025Article
- Open-access fNIRS dataset for motor imagery of lower-limb knee and ankle joint tasks.Frontiers in robotics and AI · 2025Article
- Advancements in the application of brain-computer interfaces based on different paradigms in amyotrophic lateral sclerosis.Frontiers in neuroscience · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of brain-computer interface-controlled exoskeletons promises new treatment strategies for neurorehabilitation after stroke or spinal cord injury. By converting brain/neural activity into control signals of wearable actuators, brain/neural exoskeletons (B/NEs) enable the execution of movements despite impaired motor function. Beyond the use as assistive devices, it was shown that-upon repeated use over several weeks-B/NEs can trigger motor recovery, even in chronic paralysis. Recent development of lightweight robotic actuators, comfortable and portable real-world brain recordings, as well as reliable brain/neural control strategies have paved the way for B/NEs to enter clinical care. Although B/NEs are now technically ready for broader clinical use, their promotion will critically depend on early adopters, for example, research-oriented physiotherapists or clinicians who are open for innovation. Data collected by early adopters will further elucidate the underlying mechanisms of B/NE-triggered motor recovery and play a key role in increasing efficacy of personalized treatment strategies. Moreover, early adopters will provide indispensable feedback to the manufacturers necessary to further improve robustness, applicability, and adoption of B/NEs into existing therapy plans.
Indexed as
Identifiers
What OpenQuestion holds
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.