ReviewMayo Clinic proceedings2012
Brain-computer interfaces in medicine.
Review in Mayo Clinic proceedings, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 147 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.
Somatotopic Configuration of Distal Residual Limb Tissues in Lower Extremity Amputations
A Novel Approach to Upper Extremity Amputation to Augment Volitional Control and Restore Proprioception
Who cites it
147 citing papers in PubMed, 5 syntheses or guidelines pooled it, 702 citations in OpenAlex.
- Brain-computer interface for post-stroke upper-limb recovery: a systematic review integrating clinical efficacy with neuroplasticity evidence.Frontiers in neurology · 2026Pooled it
- The impact of non-invasive brain-computer interface technology on the therapeutic effect of patients with spinal cord injury: a summary of evidence based on meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions.Frontiers in human neuroscience · 2024Pooled it
- EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Motor imagery-based brain-computer interface rehabilitation programs enhance upper extremity performance and cortical activation in stroke patients.Journal of neuroengineering and rehabilitation · 2024Trial
- Motor imagery training of goal-directed reaching in relation to imagery of reaching and grasping in healthy people.Scientific reports · 2022Trial
- Trial
- The foundational role of autonomy for brain-computer interfaces.Philosophy, ethics, and humanities in medicine : PEHM · 2026Article
- Motor Imagery Acquisition and Classification Using a Low-Cost 8-Channel EEG System in a VR ADHD Serious Game Environment: A Case Study.Sensors (Basel, Switzerland) · 2026Article
- Brain-spine interface: an exploration of a potential future treatment for spinal cord injury.Neurosurgical review · 2026Review
- Consent in flux: when brain‑computer interface embodiment undermines informed consent.BMC medical ethics · 2026Article
- PolyGraph - Flexible, Biocompatible & Electrically Optimized Graphene-Polymer Composites for Next-Generation Neural Interfaces.Advanced healthcare materials · 2026Article
- Organoid Brain-Machine-Interface Devices for Central Nervous System Repair.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Artificial intelligence in clinical physiology: System-wise applications in diagnostics, monitoring, and medical education.Journal of family medicine and primary care · 2026Article
- Decoding multi-class motor attempt from the affected unilateral limbs in chronic stroke patients.Journal of neuroengineering and rehabilitation · 2026Article
- Multi-scale EEG feature decoding with Swin Transformers for subject independent motor imagery BCIs.Scientific reports · 2026Article
- Article
- Perception of brain-computer interface implantation surgery for motor, sensory, and autonomic restoration in spinal cord injury and stroke.Frontiers in neuroscience · 2026Article
- Research on multimodal interaction intention recognition based on EEG, eye movement, and gesture signals.Scientific reports · 2025Article
87 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function.
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.