ReviewAPL bioengineering2021
Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.
Review in APL bioengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- A comprehensive evaluation framework for consumer-grade EEG devices: signal quality, robustness, and usability.Scientific reports · 2026Article
- A study on Chinese college students' acceptance of brain-computer interface technology and its underlying logic-an empirical analysis based on the extended UTAUT model.Frontiers in human neuroscience · 2026Article
- Closed-loop EEG-based neurofeedback and brain-computer interface interventions for mental health: a review.Frontiers in neuroscience · 2026Review
- A large electroencephalogram database of freewill reaching and grasping tasks for brain machine interfaces.Scientific data · 2025Article
- Neuroengineering Frontiers: A Selective Review of Neural Interfaces, Brain-Machine Interactions, and Artificial Intelligence in Neurodegenerative Diseases.Applied sciences (Basel, Switzerland) · 2025Article
- Classification of Different Motor Imagery Tasks with the Same Limb Using Electroencephalographic Signals.Sensors (Basel, Switzerland) · 2025Article
- Informed consent competency assessment for brain-computer interface clinical research and application in psychiatric disorders: A systematic review.World journal of psychiatry · 2025Article
- Motion artifact-controlled micro-brain sensors between hair follicles for persistent augmented reality brain-computer interfaces.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Several inaccurate or erroneous conceptions and misleading propaganda about brain-computer interfaces.Frontiers in human neuroscience · 2024Review
- Biohybrid neural interfaces: improving the biological integration of neural implants.Chemical communications (Cambridge, England) · 2023Review
- Assisting schizophrenia diagnosis using clinical electroencephalography and interpretable graph neural networks: a real-world and cross-site study.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
- Technical and clinical considerations for electroencephalography-based biomarkers for major depressive disorder.Npj mental health research · 2023Review
- Assistive technology: opportunities for societal inclusion of persons with disabilities and independence of the elderly.BMC biomedical engineering · 2023Article
- Applications of brain-computer interfaces in neurodegenerative diseases.Neurosurgical review · 2023Review
- Towards Cognitive Authentication for Smart Healthcare Applications.Sensors (Basel, Switzerland) · 2022Article
- The ethics of AI-assisted warfighter enhancement research and experimentation: Historical perspectives and ethical challenges.Frontiers in big data · 2022Article
- A State-of-the-Art Review of EEG-Based Imagined Speech Decoding.Frontiers in human neuroscience · 2022Review
- A Graph Fourier Transform Based Bidirectional Long Short-Term Memory Neural Network for Electrophysiological Source Imaging.Frontiers in neuroscience · 2022Article
- Possibilities in bioelectronics: Super humans or science fiction?APL bioengineering · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interfaces (BCIs) provide bidirectional communication between the brain and output devices that translate user intent into function. Among the different brain imaging techniques used to operate BCIs, electroencephalography (EEG) constitutes the preferred method of choice, owing to its relative low cost, ease of use, high temporal resolution, and noninvasiveness. In recent years, significant progress in wearable technologies and computational intelligence has greatly enhanced the performance and capabilities of EEG-based BCIs (eBCIs) and propelled their migration out of the laboratory and into real-world environments. This rapid translation constitutes a paradigm shift in human-machine interaction that will deeply transform different industries in the near future, including healthcare and wellbeing, entertainment, security, education, and marketing. In this contribution, the state-of-the-art in wearable biosensing is reviewed, focusing on the development of novel electrode interfaces for long term and noninvasive EEG monitoring. Commercially available EEG platforms are surveyed, and a comparative analysis is presented based on the benefits and limitations they provide for eBCI development. Emerging applications in neuroscientific research and future trends related to the widespread implementation of eBCIs for medical and nonmedical uses are discussed. Finally, a commentary on the ethical, social, and legal concerns associated with this increasingly ubiquitous technology is provided, as well as general recommendations to address key issues related to mainstream consumer adoption.
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.