ReviewIEEE reviews in biomedical engineering2025
Non-Invasive Brain-Computer Interfaces: State of the Art and Trends.
Review in IEEE reviews in biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
60 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Comparative Effectiveness of Noninvasive Brain-Computer Interface-Based Interventions for Upper Limb Rehabilitation in Poststroke Hemiplegia: Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- Brain-computer interface for upper limb functional recovery post-stroke: a meta-analysis of improvement in upper limb motor function and changes in neurophysiological markers.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Brain-computer interface for post-stroke upper-limb recovery: a systematic review integrating clinical efficacy with neuroplasticity evidence.Frontiers in neurology · 2026Pooled it
- Application and prospects of brain-computer interface technology for motor function reconstruction after brachial plexus injury.Annals of medicine · 2026Review
- Subject-Specific Deep Learning Model for Motor Imagery Direction Decoding.Sensors (Basel, Switzerland) · 2026Article
- SQ-HAF: Source Quality-Guided Hierarchical Adaptation and Multi-Branch Fusion for Few-Shot Cross-Subject SSVEP Recognition.Sensors (Basel, Switzerland) · 2026Article
- A Comprehensive Review of Sequence and Generative Models in Motor Imagery (MI) Classification for Brain-Computer Interfaces (BCIs).Sensors (Basel, Switzerland) · 2026Review
- Arachidonic acid metabolism in spinal cord injury.Journal of advanced research · 2026Review
- Advancing data protections for implantable brain-computer interfaces.Communications medicine · 2026Review
- Sensory-guided human-machine joint learning accelerates the acquisition of motor imagery brain computer interface control.Nature communications · 2026Article
- Adaptive Neural Reorganization Enables Real-Time Finger-Level Robotic Control in BCI-Naïve Stroke Survivors.bioRxiv : the preprint server for biology · 2026Article
- ZMW-RSVP: a time-frequency prior-guided normalization-free RSVP-BCI decoding model.Scientific reports · 2026Article
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- An Immersive P300 Brain-Computer Interface Based on 3D Morphological Stimuli and Self-Adaptive Bayesian Linear Discriminant Analysis.Biomimetics (Basel, Switzerland) · 2026Article
- Operational Transformer: An investigation of epilepsy detection.Brain topography · 2026Article
- Opposing cortical forces: Alpha slowing and sensorimotor mu acceleration during motor-related BCI training.PLoS computational biology · 2026Article
- A lower-limb motor imagery BCI using virtual reality and novel calibration strategy in post-stroke patients.Medical & biological engineering & computing · 2026Article
- Review
- The evolution of speech communication devices for anarthria: a review.Journal of neurology · 2026Review
- Quantum inspired feature engineering for explainable EEG signal classification.Scientific reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to widely influence research, clinical and recreational use. Non-invasive BCI approaches are particularly common as they can impact a large number of participants safely and at a relatively low cost. Where traditional non-invasive BCIs were used for simple computer cursor tasks, it is now increasingly common for these systems to control robotic devices for complex tasks that may be useful in daily life. In this review, we provide an overview of the general BCI framework as well as the various methods that can be used to record neural activity, extract signals of interest, and decode brain states. In this context, we summarize the current state-of-the-art of non-invasive BCI research, focusing on trends in both the application of BCIs for controlling external devices and algorithm development to optimize their use. We also discuss various open-source BCI toolboxes and software, and describe their impact on the field at large.
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.