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Brain-computer interface technology: a review of the first international meeting

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A spelling device for the paralysed

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Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans

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Slow potentials of the cerebral cortex and behavior.

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Brain function in coma, vegetative state, and related disorders

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Utilizing a Language Model to Improve Online Dynamic Data Collection in P300 Spellers

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Electroencephalography of completely locked-in state patients with amyotrophic lateral sclerosis

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Effects of a Vibro-Tactile P300 Based Brain-Computer Interface on the Coma Recovery Scale-Revised in Patients With Disorders of Consciousness

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The WIN-speller: a new intuitive auditory brain-computer interface spelling application

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Improved P300 speller performance using electrocorticography, spectral features, and natural language processing

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Ethical considerations in the use of brain-computer interfaces

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Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State

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Brain–Computer Interface Based Solutions for End-Users with Severe Communication Disorders

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Brain–computer interface and semantic classical conditioning of communication in paralysis

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Brain-computer interface for the communication of acute patients: a feasibility study and a randomized controlled trial comparing performance with healthy participants and a traditional assistive device

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Multiple Scale Convolutional Few-Shot Learning Networks for Online P300-Based Brain–Computer Interface and Its Application to Patients With Disorder of Consciousness

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Evaluation of Brain-computer Interfaces in Accessing Computer and other Devices by People with Severe Motor Impairments

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Electrophysiological correlates of neurodegeneration in motor and non-motor brain regions in amyotrophic lateral sclerosis—implications for brain–computer interfacing

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Neurophysiological aspects of the completely locked-in syndrome in patients with advanced amyotrophic lateral sclerosis

Khalili‐Ardali, M., Wu, S., Tonin, A., Birbaumer, N., & Chaudhary, U. (2021) · Clinical Neurophysiology · doi:10.1016/j.clinph.2021.01.013 · Cited by 25

Brain-Computer Interaction and Medical Access to the Brain: Individual, Social and Ethical Implications

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A Multi-Class Tactile Brain–Computer Interface Based on Stimulus-Induced Oscillatory Dynamics

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Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

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Decoding Covert Somatosensory Attention by a BCI System Calibrated With Tactile Sensation

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Visual Fixation Assessment in Patients with Disorders of Consciousness Based on Brain-Computer Interface

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Decoding Steady-State Visual Evoked Potentials From Electrocorticography

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Toward a reliable gaze-independent hybrid BCI combining visual and natural auditory stimuli

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A human-computer interface based on the “voluntary” pupil accommodative response

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Single-paradigm and hybrid brain computing interfaces and their use by disabled patients

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A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state

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Semantic and BCI-performance in completely paralyzed patients: Possibility of language attrition in completely locked in syndrome

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Investigating the Emotiv EPOC for cognitive control in limited training time

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New horizons in brain-computer interface research

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Brain–Computer Interface Technology

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Dry and Water-Based EEG Electrodes in SSVEP-Based BCI Applications

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Prediction of P300 BCI Aptitude in Severe Motor Impairment

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Review of brain computer interface application in diagnosing dyslexia

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MindEdit: A P300-based text editor for mobile devices

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Assessment of Visual Pursuit in Patients With Disorders of Consciousness Based on a Brain-Computer Interface

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Employing an active mental task to enhance the performance of auditory attention-based brain–computer interfaces

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P300 latency jitter and its correlates in people with amyotrophic lateral sclerosis

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Evaluation of the performances of different P300 based brain–computer interfaces by means of the efficiency metric

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A Hybrid Brain–Computer Interface Combining P300 Potentials and Emotion Patterns for Detecting Awareness in Patients With Disorders of Consciousness

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An EEG & eye-tracking dataset of ALS patients & healthy people during eye-tracking-based spelling system usage

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An automatic channel selection method based on the standard deviation of wavelet coefficients for motor imagery based brain–computer interfacing

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A Brain–Computer Interface Based on Three-Dimensional Stereo Stimuli for Assisting Clinical Object Recognition Assessment in Patients With Disorders of Consciousness

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Locked Out

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Real-time Decoding of EEG Gait Intention for Controlling a Lower-limb Exoskeleton System

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Assessment of high-frequency steady-state visual evoked potentials from below-the-hairline areas for a brain-computer interface based on Depth-of-Field

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EEG power spectral density in locked-in and completely locked-in state patients: a longitudinal study

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Brain–Computer Interfaces for Communication and Control in Locked-in Patients

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Robotic Technologies and Fundamental Rights

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Real-Time Myocontrol of a Human–Computer Interface by Paretic Muscles After Stroke

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Brain Computer Interfaces for Assisted Communication in Paralysis and Quality of Life

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Semantic Classical Conditioning and Brain-Computer Interface Control: Encoding of Affirmative and Negative Thinking

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Recovery of the motor function of the arm with the aid of a hand exoskeleton controlled by a brain–computer interface in a patient with an extensive brain lesion

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Communication and Control by Listening: Toward Optimal Design of a Two-Class Auditory Streaming Brain-Computer Interface

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A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome

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Brain Teleoperation Control of a Nonholonomic Mobile Robot Using Quadrupole Potential Function

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Brain–Machine Interfaces for Communication in Complete Paralysis: Ethical Implications and Challenges

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Future Developments in Brain/Neural–Computer Interface Technology

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Tactile event-related potentials in amyotrophic lateral sclerosis (ALS): Implications for brain-computer interface

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Modulation of Event-related Desynchronization duringMotor Imagery with Transcranial Direct Current Stimulationin a Patient with Severe Hemiparetic Stroke: A Case Report

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Case series: Slowing alpha rhythm in late-stage ALS patients

Hohmann, M. R., Fomina, T., Jayaram, V., Emde, T., Just, J., Synofzik, M., Schölkopf, B., Schöls, L. J., & Grosse‐Wentrup, M. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.11.013 · Cited by 15

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

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Revisiting embodiment for brain–computer interfaces

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A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis

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The N400 for brain computer interfacing: complexities and opportunities

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Mental Strategies in a P300-BCI: Visuomotor Transformation Is an Option

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Editorial Expression of Concern for multiple articles

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Nonspecific Visuospatial Imagery as a Novel Mental Task for Online EEG-Based BCI Control

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Visuo-auditory stimuli with semantic, temporal and spatial congruence for a P300-based BCI: An exploratory test with an ALS patient in a completely locked-in state

Pires, G., Barbosa, S. M., Nunes, U., & Gonçalves, E. (2022) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2022.109661 · Cited by 18

Brain-brain integration in 2035: metaphysical and ethical implications

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Characterizing Computer Access Using a One-Channel EEG Wireless Sensor

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Improving the Efficacy of ERP-Based BCIs Using Different Modalities of Covert Visuospatial Attention and a Genetic Algorithm-Based Classifier

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Learning from brain control: clinical application of brain–computer interfaces

Birbaumer, N., & Chaudhary, U. (2015) · e-Neuroforum · doi:10.1007/s13295-015-0015-x · Cited by 12

KITE-BCI: A brain-computer interface system for functional electrical stimulation therapy

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Brain–Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness

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Toward a Semi-Self-Paced EEG Brain Computer Interface: Decoding Initiation State from Non-Initiation State in Dedicated Time Slots

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Emerging Ethical Issues Related to the Use of Brain-Computer Interfaces for Patients with Total Locked-in Syndrome

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Aristotle Meets Zeno: Psychophysiological Evidence

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Brain-Computer Interfaces for Human Augmentation

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Design of auditory P300-based brain-computer interfaces with a single auditory channel and no visual support

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MST-DGCN: A Multi-Scale Spatio-Temporal and Dynamic Graph Convolution Fusion Network for Electroencephalogram Recognition of Motor Imagery

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Brain-Computer Interface for Assessing Consciousness in Severely Brain-Injured Patients

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Cognitive assessment of executive functions using brain computer interface and eye-tracking

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An online BCI game based on the decoding of users' attention to color stimulus

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Covert Intention to Answer “Yes” or “No” Can Be Decoded from Single-Trial Electroencephalograms (EEGs)

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Brain–Computer Interface in Neurorehabilitation

Birbaumer, N., & Sauseng, P. (2009) · The frontiers collection · doi:10.1007/978-3-642-02091-9_9 · Cited by 10

A Progressive Multi-Domain Adaptation Network With Reinforced Self-Constructed Graphs for Cross-Subject EEG-Based Emotion and Consciousness Recognition

Chen, R. R., Xie, C., Zhang, J., You, Q., & Pan, J. (2025) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2025.3603190 · Cited by 9

Epidural electrocorticography for monitoring of arousal in locked-in state

Martens, S., Bensch, M., Halder, S., Hill, J., Nijboer, F., Ramos‐Murguialday, A., Schölkopf, B., Birbaumer, N., & Gharabaghi, A. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00861 · Cited by 9

A Spelling Paradigm With an Added Red Dot Improved the P300 Speller System Performance

Wu, Y. X., Zhou, W., Lu, Z., & Li, Q. (2020) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2020.589169 · Cited by 9

Accurate Decoding of Short, Phase-Encoded SSVEPs

Amer, A. Y. A., Wittevrongel, B., & Hulle, M. M. V. (2018) · Sensors · doi:10.3390/s18030794 · Cited by 9

CLASSIFICATION OF MOTOR IMAGERY FOR BRAIN-COMPUTER INTERFACES

Szachewicz, P. (2013) · Cited by 9

Feasibility of using discrete Brain Computer Interface for people with Multiple Sclerosis

Shiels, T. A., Oxley, T. J., Fitzgerald, P. B., Opie, N. L., Wong, Y. T., Grayden, D. B., & John, S. E. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9629518 · Cited by 8

Identifying potential training factors in a vibrotactile P300-BCI

Eidel, M., & Kübler, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-18088-w · Cited by 8

The BciAi4SLA Project: Towards a User-Centered BCI

Cristina Gena, A., Hilviu, D., Chiarion, G., Roatta, S., Bosco, F. M., Calvo, A., Mattutino, C., & Vincenzi, S. (2023) · Electronics · doi:10.3390/electronics12051234 · Cited by 9

Experiences of family of individuals in a locked in, minimally conscious state, or vegetative state with the health care system

Munce, S., Webster, F., Christian, J. B., González-Lara, L. E., Owen, A. M., & Weijer, C. (2020) · Brain Injury · doi:10.1080/02699052.2020.1858494 · Cited by 8

Improving longitudinal P300-BCI performance for people with ALS using a data augmentation and jitter correction approach

Zisk, A. H., Borgheai, S. B., McLinden, J., Deligani, R. J., & Shahriari, Y. (2021) · Brain-Computer Interfaces · doi:10.1080/2326263x.2021.2014678 · Cited by 8

Communication in locked-in state after brainstem stroke: a brain-computer-interface approach.

Chaudhary, U., & Birbaumer, N. (2015) · PubMed Central · doi:10.3978/j.issn.2305-5839.2015.02.27 · Cited by 8

Semantic conditioning of salivary pH for communication

Ruf, C. A., Massari, D. D., Wagner-Podmaniczky, F., Matuz, T., & Birbaumer, N. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.07.001 · Cited by 8

Home smart home: brain-computer interface control for real smart home environments

Carabalona, R., Grossi, F., Tessadri, A., Caracciolo, A., Castiglioni, P., & Munari, I. D. (2010) · International Convention on Rehabilitation Engineering & Assistive Technology · Cited by 8

PhyAAt: Physiology of Auditory Attention to Speech DatasetPreprint

Bajaj, N., Carrión, J. R., & Bellotti, F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.11577 · Cited by 10

Decoding imagined movement in people with multiple sclerosis for brain–computer interface translation

Russo, J. S., Shiels, T. A., Lin, C., John, S. E., & Grayden, D. B. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adaa1d · Cited by 7

LIS and BCIs: a Local, Pluralist, and Pragmatist Approach to 4E Cognition

Hibbert, R. (2016) · Neuroethics · doi:10.1007/s12152-016-9267-6 · Cited by 7

The Elusive Goal of BCI-based Communication with CLIS-ALS Patients

Grosse‐Wentrup, M. (2019) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/iww-bci.2019.8737310 · Cited by 7

Neuropsychological and neurophysiological aspects of brain‐computer‐interface (BCI) control in paralysis

Chaudhary, U., Mrachacz‐Kersting, N., & Birbaumer, N. (2020) · The Journal of Physiology · doi:10.1113/jp278775 · Cited by 88

Learning from brain control: clinical application of brain–computer interfaces

Birbaumer, N., & Chaudhary, U. (2015) · e-Neuroforum · doi:10.1515/s13295-015-0015-x · Cited by 7

The Elusive Goal of BCI-based Communication with CLIS-ALS Patients

Grosse‐Wentrup, M. (2019) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/iww-bci.2019.8737310 · Cited by 7

Direct Brain Control and Communication in Paralysis

Birbaumer, N., Gallegos-Ayala, G., Wildgruber, M., Silvoni, S., & Soekadar, S. R. (2013) · Brain Topography · doi:10.1007/s10548-013-0282-1 · Cited by 76

Brain–computer interfaces: communication and restoration of movement in paralysis

Birbaumer, N., & Cohen, L. G. (2007) · The Journal of Physiology · doi:10.1113/jphysiol.2006.125633 · Cited by 763