Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/okbalefthanded/awesome-bci-reviews

Curated list of Brain-Computer Interface peer-reviewd reviews and surveys
https://github.com/okbalefthanded/awesome-bci-reviews

List: awesome-bci-reviews

Last synced: 3 months ago
JSON representation

Curated list of Brain-Computer Interface peer-reviewd reviews and surveys

Awesome Lists containing this project

README 

        
# Awesome-BCI-Reviews

Curated list of Brain-Computer Interface peer-reviewd published reviews and surveys ordered by year of publication.



[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)



[2000](#2000) | [2003](#2003) | [2007](#2007) | [2010](#2010) | [2011](#2011) | [2012](#2012) | [2013](#2013) | [2014](#2014) | [2015](#2015) | [2016](#2016) |

[2017](#2017) | [2018](#2018) | [2019](#2019) | [2020](#2020) | [2021](#2021) | [2022](#2022) | [2023](#2023) | [2024](#2024) 



# 2000

- [Brain–Computer Interface Technology : A Review of the First International Meeting](https://ieeexplore.ieee.org/document/847807/)



# 2003

- [Learning to control brain activity: A review of the production and control of EEG components for driving brain–computer interface (BCI) systems](https://www.sciencedirect.com/science/article/abs/pii/S0278262603000368)



# 2007

- [A review of classification algorithms for EEG-based brain-computer interfaces](https://iopscience.iop.org/article/10.1088/1741-2560/4/2/R01)

- [A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals](https://iopscience.iop.org/article/10.1088/1741-2560/4/2/R03)

- [EMG and EOG artifacts in brain computer interface systems: A survey.](https://www.sciencedirect.com/science/article/abs/pii/S1388245706015124)



# 2008

- [Brain–computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients?](https://www.sciencedirect.com/science/article/abs/pii/S1388245708009115)



# 2009

- [Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects](https://ieeexplore.ieee.org/abstract/document/5342720)



# 2010

- [Combining brain–computer interfaces and assistive technologies: state-of-the-art and challenges](https://www.frontiersin.org/articles/10.3389/fnins.2010.00161/full)

- [Enhancing human-computer interaction with input from active and passive brain-computer interfaces. (In: Brain-computer interfaces.)](https://link.springer.com/chapter/10.1007/978-1-84996-272-8_11)

- [Towards inexpensive BCI control for wheelchair navigation in the enabled environment - A hardware survey](https://link.springer.com/chapter/10.1007/978-3-642-15314-3_32)

- [A survey of stimulation methods used in SSVEP-based BCIs](https://www.hindawi.com/journals/cin/2010/702357/)

- [The Berlin Brain–Computer Interface: Non-Medical Uses of BCI Technology](https://www.frontiersin.org/articles/10.3389/fnins.2010.00198/full)



# 2011

- [Toward smarter BCIs: extending BCIs through hybridization and intelligent Control](https://iopscience.iop.org/article/10.1088/1741-2560/9/1/013001)

- [Tools for brain-computer interaction: a general concept for a hybrid BCI](https://www.frontiersin.org/articles/10.3389/fninf.2011.00030/full)

- [A Review of Asynchronous Electroencephalogram-based Brain Computer Interface Systems](https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwi849a3h6ryAhXtyIUKHdvaA6wQFnoECAMQAQ&url=http%3A%2F%2Fwww.ipcbee.com%2Fvol11%2F11-T025.pdf&usg=AOvVaw0KvklvrgRN3E4Z87aOkb9b)

- [Critical issues in state-of-the-art brain-computer interface signal processing](https://iopscience.iop.org/article/10.1088/1741-2560/8/2/025002)

- [Optimizing the P300-based brain-computer interface: current status, limitations and future directions.](https://iopscience.iop.org/article/10.1088/1741-2560/8/2/025003)

- [Brain-computer interfaces using electrocorticographic signals.](https://ieeexplore.ieee.org/document/6047564)

- [Challenges and opportunities for next-generation intracortically based neural prostheses](https://ieeexplore.ieee.org/document/5699350)

- [A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs) (in BCI state of the art summary)](https://www.springer.com/gp/book/9783642360824)



# 2012

- [P300 brain computer interface: current challenges and emerging trends.](https://www.frontiersin.org/articles/10.3389/fneng.2012.00014/full)

- [Brain–computer interfaces for multimodal interaction: a survey and principles](https://www.tandfonline.com/doi/abs/10.1080/10447318.2011.582022)

- [From spinal central pattern generators to cortical network: Integrated BCI for walking rehabilitation](https://www.hindawi.com/journals/np/2012/375148/)

- [A review of P300, SSVEP, and hybrid P300/SSVEP brain computer interface systems. (In: Brain-computer interface systems - recent progress and future prospects. InTech)](https://www.intechopen.com/chapters/44907)

- [Review of the BCI competition IV](https://www.frontiersin.org/articles/10.3389/fnins.2012.00055/full)

- [Brain computer interfaces, a review.](https://www.mdpi.com/1424-8220/12/2/1211)

- [A comparison of classification techniques for a gaze-independent P300-based brain-computer interface.](https://iopscience.iop.org/article/10.1088/1741-2560/9/4/045012)

- [Toward functioning and usable brain–computer interfaces (BCIs): A literature review](https://www.tandfonline.com/doi/full/10.3109/17483107.2011.589486)

- [Eye-gaze independent EEG-based brain–computer interfaces for communication](https://iopscience.iop.org/article/10.1088/1741-2560/9/4/045001)



# 2013

- [A review of hybrid brain-computer interface systems](https://www.hindawi.com/journals/ahci/2013/187024/)

- [Games, gameplay, and BCI: The state of the art](https://ieeexplore.ieee.org/document/6518141)

- [Adapting the P300-based brain-computer interface for gaming: A review](https://ieeexplore.ieee.org/document/6401177)

- [Principles of hybrid brain–computer interfaces. (In: Towards practical brain computer interface)](https://link.springer.com/chapter/10.1007/978-3-642-29746-5_18)

- [Hybrid optical–electrical brain computer interfaces, practices and possibilities. (In: Towards practical brain-computer interfaces.)](https://link.springer.com/chapter/10.1007/978-3-642-29746-5_2)

- [Brain computer interfacing: a multimodal perspective](http://koreascience.or.kr/article/JAKO201319133640242.page)

- [A review of kernels on covariance matrices for BCI applications](https://ieeexplore.ieee.org/document/6661972)

- [An analysis of performance evaluation for motor-imagery based BCI](https://iopscience.iop.org/article/10.1088/1741-2560/10/3/031001)

- [EEG-Based Brain-Computer Interfaces: A Thorough Literature Survey](https://www.tandfonline.com/doi/abs/10.1080/10447318.2013.780869)

- [EEG-Based Brain-Controlled Mobile Robots: A Survey](https://ieeexplore.ieee.org/document/6461528)



# 2014

- [Visual and auditory brain-computer interfaces](https://ieeexplore.ieee.org/document/6712069)

- [Effectiveness of the P3-speller in brain-computer interfaces for amyotrophic lateral sclerosis patients: a systematic review and meta-analysis.](https://www.frontiersin.org/articles/10.3389/fneng.2014.00012/full)

- [Noninvasive brain-computer interfaces for augmentative and alternative communication.](https://ieeexplore.ieee.org/document/6684304)

- [Dry EEG electrodes](https://www.mdpi.com/1424-8220/14/7/12847)

- [Performance measurement for brain–computer or brain–machine interfaces: a tutorial](https://iopscience.iop.org/article/10.1088/1741-2560/11/3/035001)

- [A survey of affective brain computer interfaces: principles, state-of-the-art, and challenges](https://www.tandfonline.com/doi/abs/10.1080/2326263X.2014.912881)

- [Brain–Computer Interfaces Using Sensorimotor Rhythms: Current State and Future Perspectives](https://ieeexplore.ieee.org/document/6775293)



# 2015

- [A review on transfer learning for brain-computer interface classification](https://ieeexplore.ieee.org/document/7288989)

- [Steady-State Somatosensory Evoked Potential for Brain-Computer Interface—Present and Future](https://www.frontiersin.org/articles/10.3389/fnhum.2015.00716/full)

- [EEG artifact removal-state-of-the-art and guidelines.](https://iopscience.iop.org/article/10.1088/1741-2560/12/3/031001)

- [Student Teaching and Research Laboratory Focusing on Brain-computer Interface Paradigms - A Creative Environment for Computer Science Students -](https://ieeexplore.ieee.org/document/7319188)

- [Learning from more than one data source: data fusion techniques for sensorimotor rhythm-based Brain-Computer Interfaces](https://ieeexplore.ieee.org/document/7110317)

- [Towards Noninvasive Hybrid Brain–Computer Interfaces: Framework, Practice, Clinical Application, and Beyond](https://ieeexplore.ieee.org/document/7109824)

- [Signal Processing Approaches to Minimize or Suppress Calibration Time in Oscillatory Activity-Based Brain–Computer Interfaces](https://ieeexplore.ieee.org/document/7109822)

- [A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0140703)

- [Multi-modal and multi-brain-computer interfaces: A review](https://ieeexplore.ieee.org/document/7459835)

- [fNIRS-based brain-computer interfaces: a review](https://www.frontiersin.org/articles/10.3389/fnhum.2015.00003/full)



# 2016

- [Recent advances and open challenges in hybrid brain-computer interfacing: a technological review of non-invasive human research](https://www.tandfonline.com/doi/abs/10.1080/2326263X.2015.1134958)

- [Scientific profile of brain–computer interfaces: Bibliometric analysis in a 10-year period](https://www.sciencedirect.com/science/article/abs/pii/S0304394016307741?via%3Dihub)

- [A Review of Electrodes for the Electrical Brain Signal Recording](https://link.springer.com/article/10.1007/s13534-016-0235-1)

- [Integrating language models into classifiers for BCI communication: a review](https://iopscience.iop.org/article/10.1088/1741-2560/13/3/031002)

- [Review of real brain-controlled wheelchairs](https://iopscience.iop.org/article/10.1088/1741-2560/13/6/061001)

- [Stimuli design for SSVEP-based brain computer-interface](https://www.researchgate.net/publication/304670441_Stimuli_design_for_SSVEP-based_brain_computer-interface)

- [The Berlin Brain-Computer Interface: Progress Beyond Communication and Control](https://www.frontiersin.org/articles/10.3389/fnins.2016.00530/full)

- [Beyond ‘communication and control’: towards ethically complete rationales for brain-computer interface research](https://www.tandfonline.com/doi/abs/10.1080/2326263X.2016.1213603?journalCode=tbci20)

- [Multimodal BCIs: Target Detection, Multidimensional Control, and Awareness Evaluation in Patients with Disorder of Consciousness](https://ieeexplore.ieee.org/abstract/document/7299246)

- [Advances in user-training for mental-imagery-based BCI control](https://www.sciencedirect.com/science/article/abs/pii/S0079612316300061?via%3Dihub)

- [3D graphics, virtual reality, and motion-onset visual evoked potentials in neurogaming](https://www.sciencedirect.com/science/article/abs/pii/S0079612316300929?via%3Dihub)

- [Robotic and Virtual Reality BCIs Using Spatial Tactile and Auditory Oddball Paradigms](https://www.frontiersin.org/articles/10.3389/fnbot.2016.00020/full)



# 2017

- [A review and experimental study on application of classifiers and evolutionary algorithms in EEG based brain-machine interface systems](https://iopscience.iop.org/article/10.1088/1741-2552/aa8063)

- [Riemannian Approaches in Brain-Computer Interfaces: A Review](https://ieeexplore.ieee.org/document/7740054)

- [Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review](https://www.tandfonline.com/doi/abs/10.1080/2326263X.2017.1297192?journalCode=tbci20)

- [A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176674)

- [Hybrid brain-computer interface techniques for improved classification accuracy and increased number of commands: A review](https://www.frontiersin.org/articles/10.3389/fnbot.2017.00035/full)

- [A review of rapid serial visual presentation-based brain-computer interfaces](https://iopscience.iop.org/article/10.1088/1741-2552/aa9817)

- [Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review ](https://iopscience.iop.org/article/10.1088/1741-2552/14/1/011001)

- [Best practice for single-trial detection of event-related potentials: Application to brain-computer interfaces](https://www.sciencedirect.com/science/article/abs/pii/S016787601630633X?via%3Dihub)

- [Brain computer interface_ control signals review](https://www.sciencedirect.com/science/article/abs/pii/S0925231216312152)

- [Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation](https://journals.physiology.org/doi/full/10.1152/physrev.00027.2016?rfr_dat=cr_pub++0pubmed&url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org)

- [Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system](https://www.sciencedirect.com/science/article/abs/pii/S1746809416301331)

- [BRAIN-COMPUTER INTERFACES AND AUGMENTED REALITY: A STATE OF THE ART](https://hal.inria.fr/hal-01625167/document)

- [Brain computer interface systems using non-invasive electroencephalogram signal: A literature review](https://ieeexplore.ieee.org/document/8280071)



# 2018

- [A comprehensive review of EEG-based brain-computer interface paradigms](https://iopscience.iop.org/article/10.1088/1741-2552/aaf12e)

- [A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update](https://iopscience.iop.org/article/10.1088/1741-2552/aab2f2/meta)

- [Brain-Machine Interfaces for Controlling Lower-Limb Powered Robotic Systems](https://iopscience.iop.org/article/10.1088/1741-2552/aaa8c0)

- [A survey on unmanned aerial vehicle remote control using brain-computer interface](https://ieeexplore.ieee.org/document/8362734)

- [Asilomar Survey: Researcher Perspectives on Ethical Principles and Guidelines for BCI Research](https://www.tandfonline.com/doi/abs/10.1080/2326263X.2018.1530010?journalCode=tbci20)

- [To train or not to train? A survey on training of feature extraction methods for SSVEP-based BCIs](https://iopscience.iop.org/article/10.1088/1741-2552/aaca6e)

- [Brain–Computer Interface Spellers: A Review](https://www.mdpi.com/2076-3425/8/4/57)

- [Brain-machine interfaces for rehabilitation in stroke: A review](https://content.iospress.com/articles/neurorehabilitation/nre172394)

- [A review of disability EEG based wheelchair control system: Coherent taxonomy, open challenges and recommendations](https://www.sciencedirect.com/science/article/abs/pii/S0169260718304620)



# 2019

- [Deep learning-based electroencephalography analysis: a systematic review](https://iopscience.iop.org/article/10.1088/1741-2552/ab260c)

- [Single-paradigm and hybrid brain computing interfaces and their use by disabled patients](https://iopscience.iop.org/article/10.1088/1741-2552/ab2706)

- [A Review of Error-Related Potential-Based Brain–Computer Interfaces for Motor Impaired People](https://ieeexplore.ieee.org/document/8849999)

- [Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications](https://www.hindawi.com/journals/cin/2019/3807670/)

- [Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects](https://www.frontiersin.org/articles/10.3389/fnhum.2019.00013/full)

- [Brain–Computer Interface Games Based on Consumer-Grade EEG Devices: A Systematic Literature Review](https://www.tandfonline.com/doi/full/10.1080/10447318.2019.1612213)



# 2020

- [BCI for stroke rehabilitation: Motor and beyond](https://iopscience.iop.org/article/10.1088/1741-2552/aba162)

- [The N400 for brain computer interfacing: complexities and opportunities](https://iopscience.iop.org/article/10.1088/1741-2552/ab702e)

- [Spatial Filtering in SSVEP-based BCIs: Unified Framework and New Improvements](https://ieeexplore.ieee.org/document/9006809)

- [Brain-computer interface-based humanoid control: A review](https://www.mdpi.com/1424-8220/20/13/3620)

- [Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals](https://link.springer.com/article/10.1007/s11370-020-00328-5)

- [Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review](https://www.frontiersin.org/articles/10.3389/fnbot.2020.00025/full)

- [A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges](https://www.sciencedirect.com/science/article/abs/pii/S0165027020303411)  

- [A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers](https://iopscience.iop.org/article/10.1088/1741-2552/abc902)

- [30+ years of P300 brain–computer interfaces](https://onlinelibrary.wiley.com/doi/abs/10.1111/psyp.13569)

- [Application of Transfer Learning in EEG Decoding Based on Brain-Computer Interfaces: A Review](https://www.mdpi.com/1424-8220/20/21/6321)

- [Data Analytics in Steady-State Visual Evoked Potential-Based Brain–Computer Interface: A Review](https://ieeexplore.ieee.org/document/9170622)

- [Brain–Computer Interface Software: A Review and Discussion](https://ieeexplore.ieee.org/document/8995646)

- [Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application](https://www.sciencedirect.com/science/article/pii/S0010482520302031)

- [An empirical survey of electroencephalography-based brain-computer interfaces](https://www.degruyter.com/document/doi/10.1515/bams-2019-0053/html?lang=en)

- [Hybrid control approaches for hands-free high level human–computer interface-a review](https://www.tandfonline.com/doi/abs/10.1080/03091902.2020.1838642?journalCode=ijmt20)

- [A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback](https://www.frontiersin.org/articles/10.3389/fnins.2020.00528/full)

- [Sensor Modalities for Brain-Computer Interface Technology: A Comprehensive Literature Review](https://journals.lww.com/neurosurgery/Abstract/2020/02000/Sensor_Modalities_for_Brain_Computer_Interface.22.aspx)



# 2021

- [Direct-Sense Brain–Computer Interfaces and Wearable Computers](https://ieeexplore.ieee.org/document/9302890)

- [Interface, interaction, and intelligence in generalized brain–computer interfaces](https://doi.org/10.1016/j.tics.2021.04.003)

- [Signal Generation, Acquisition, and Processing in Brain Machine Interfaces: A Unified Review](https://www.frontiersin.org/articles/10.3389/fnins.2021.728178/full)

- [A Survey on Deep Learning-Based Short/Zero-Calibration Approaches for EEG-Based Brain–Computer Interfaces](https://www.frontiersin.org/articles/10.3389/fnhum.2021.643386/full)

- [EEG-based brain–computer interfaces exploiting steady-state somatosensory-evoked potentials: a literature review](https://iopscience.iop.org/article/10.1088/1741-2552/ac2fc4)

- [Brain–computer interfaces based on code-modulated visual evoked potentials (c-VEP): a literature review](https://iopscience.iop.org/article/10.1088/1741-2552/ac38cf)

- [A Systematic Review on Motor-Imagery Brain-Connectivity-Based Computer Interfaces](https://ieeexplore.ieee.org/document/9578928)

- [Brain–Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance](https://www.mdpi.com/2076-3425/11/4/450)

- [Brain-Controlled Wheelchair Review: From Wet Electrode to Dry Electrode, from Single Modal to Hybrid Modal, from Synchronous to Asynchronous](https://ieeexplore.ieee.org/document/9398666)

- [A systematic review on hybrid EEG/fNIRS in brain-computer interface](https://www.sciencedirect.com/science/article/abs/pii/S1746809421001920)

- [Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review](https://www.mdpi.com/2076-3425/11/1/75)

- [Review on Motor Imagery Based EEG Signal Classification for BCI Using Deep Learning Techniques](https://link.springer.com/chapter/10.1007/978-3-030-70917-4_15)

- [Mind the gap: State-of-the-art technologies and applications for EEG-based brain–computer interfaces](https://pubs.aip.org/aip/apb/article/5/3/031507/149807/Mind-the-gap-State-of-the-art-technologies-and)

- [Data Augmentation for Deep Neural Networks Model in EEG Classification Task: A Review](https://www.frontiersin.org/articles/10.3389/fnhum.2021.765525/full)

- [Review of brain encoding and decoding mechanisms for EEG-based brain–computer interface](https://link.springer.com/article/10.1007/s11571-021-09676-z)

- [Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions](https://www.frontiersin.org/articles/10.3389/fnhum.2021.772837/full)



# 2022

- [Review of Machine Learning Techniques for EEG Based Brain Computer Interface](https://link.springer.com/article/10.1007/s11831-021-09684-6)

- [Brain–Computer Interface-Controlled Exoskeletons in Clinical Neurorehabilitation: Ready or Not?](https://journals.sagepub.com/doi/full/10.1177/15459683221138751)

- [EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review](https://www.frontiersin.org/articles/10.3389/fnhum.2022.1040816/full)

- [EEG hybrid brain-computer interfaces: A scoping review applying an existing hybrid-BCI taxonomy and considerations for pediatric applications](https://www.frontiersin.org/articles/10.3389/fnhum.2022.1007136/full)

- [Advances in P300 brain–computer interface spellers: toward paradigm design and performance evaluation](https://www.frontiersin.org/articles/10.3389/fnhum.2022.1077717/full)

- [Review of the State-of-the-Art of Brain-Controlled Vehicles](https://ieeexplore.ieee.org/document/9499083)

- [Transfer Learning for EEG-Based Brain–Computer Interfaces: A Review of Progress Made Since 2016](https://ieeexplore.ieee.org/document/9134411)

- [EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives](https://www.mdpi.com/2306-5354/9/12/726)

- [Deep Learning in EEG: Advance of the Last Ten-Year Critical Period](https://ieeexplore.ieee.org/document/9430619)

- [EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0269001)

  

# 2023

- [Status of deep learning for EEG-based brain–computer interface applications](https://www.frontiersin.org/articles/10.3389/fncom.2022.1006763/full)

- [Single trial detection of error-related potentials in brain–machine interfaces: a survey and comparison of methods](https://iopscience.iop.org/article/10.1088/1741-2552/acabe9)

- [A survey of deep learning-based classification methods for steady-state visual evoked potentials](https://www.tandfonline.com/doi/full/10.1080/27706710.2023.2181102)

- [An Analysis of Deep Learning Models in SSVEP-Based BCI: A Survey](https://www.mdpi.com/2076-3425/13/3/483)

- [How Visual Stimuli Evoked P300 is Transforming the Brain–Computer Interface Landscape: A PRISMA Compliant Systematic Review](https://ieeexplore.ieee.org/document/10049170)

- [Machine learning techniques for electroencephalogram based brain-computer interface: A systematic literature review](https://www.sciencedirect.com/science/article/pii/S2665917423001599)

- [Generative Adversarial Networks for Electroencephalogram Signal Analysis: A Mini Review](https://ieeexplore.ieee.org/document/10078666)

- [A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome](https://link.springer.com/article/10.1007/s11571-023-09995-3)

- [Methods for Motion Artifact Reduction in Online Brain-Computer Interface Experiments: A Systematic Review](https://www.frontiersin.org/articles/10.3389/fnhum.2023.1251690)

- [Two is better? combining EEG and fMRI for BCI and neurofeedback: a systematic review](https://iopscience.iop.org/article/10.1088/1741-2552/ad06e1)

- [fNIRS-EEG BCIs for Motor Rehabilitation: A Review](https://www.mdpi.com/2306-5354/10/12/1393)

- [Deep Learning in EEG-Based BCIs: A Comprehensive Review of Transformer Models, Advantages, Challenges, and Applications](https://ieeexplore.ieee.org/abstract/document/10305163)

- [Review of public motor imagery and execution datasets in brain-computer interfaces](https://www.frontiersin.org/articles/10.3389/fnhum.2023.1134869/full)

- [Generative adversarial networks in EEG analysis: an overview](https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01169-w)

- [A Review of Deep Learning Methods for Cross-subject Rapid Serial Visual Presentation Detection in World Robot Contest 2022](https://journals.sagepub.com/doi/full/10.26599/BSA.2023.9050013)

- [Wearable Brain–Computer Interfaces Based on Steady-State Visually Evoked Potentials and Augmented Reality: A Review](https://ieeexplore.ieee.org/document/10161603)

    

# 2024

- [An in-depth survey on Deep Learning-based Motor Imagery Electroencephalogram (EEG) classification](https://www.sciencedirect.com/science/article/pii/S093336572300252X?via%3Dihub)

- [An Analysis of Traditional Methods and Deep Learning Methods in SSVEP-Based BCI: A Survey](https://www.mdpi.com/2079-9292/13/14/2767)

- [Data Constraints and Performance Optimization for Transformer-Based Models in EEG-Based Brain-Computer Interfaces: A Survey](https://ieeexplore.ieee.org/document/10509679)

- [Speech imagery decoding using EEG signals and deep learning: A survey](https://ieeexplore.ieee.org/abstract/document/10605127)

- [Explainable artificial intelligence approaches for brain–computer interfaces: a review and design space](https://iopscience.iop.org/article/10.1088/1741-2552/ad6593)



# Contribution

contributions are welcome, just add a missing article and send a pull request.