A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

Abstract

This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

Keywords

Computer scienceElectroencephalographyBrain–computer interfaceArtificial intelligenceAlgorithmPattern recognition (psychology)PsychologyNeuroscience

MeSH Terms

AlgorithmsAnimalsBrainBrain-Computer InterfacesDeep LearningElectroencephalographyHumansSignal ProcessingComputer-AssistedTime Factors

Affiliated Institutions

Related Publications

Multiway analysis of epilepsy tensors

Evrim Acar , Canan Aykut Bingöl , Haluk O. Bingol +2 more

Abstract Motivation: The success or failure of an epilepsy surgery depends greatly on the localization of epileptic focus (origin of a seizure). We address the problem of identi...

2007 Bioinformatics 278 citations

EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces

Vernon J. Lawhern , Amelia J. Solon , Nicholas R. Waytowich +9 more

Our results suggest that EEGNet is robust enough to learn a wide variety of interpretable features over a range of BCI tasks. Our models can be found at: https://github.com/vlaw...

2018 Journal of Neural Engineering 3477 citations

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Ningning Ma , Xiangyu Zhang , Hai-Tao Zheng +1 more

2018 Lecture notes in computer science 6005 citations

A Comprehensive Survey on Graph Neural Networks

Zong-Han Wu , Shirui Pan , Fengwen Chen +9 more

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language u...

2020 IEEE Transactions on Neural Networks ... 7809 citations

g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

Uku Raudvere , Liis Kolberg , Ivan Kuzmin +4 more

Abstract Biological data analysis often deals with lists of genes arising from various studies. The g:Profiler toolset is widely used for finding biological categories enriched ...

2019 Nucleic Acids Research 5069 citations

Publication Info

Year: 2018
Type: review
Volume: 15
Issue: 3
Pages: 031005-031005
Citations: 1924
Access: Closed

External Links

Download PDF (Free) View on DOI.org PubMed Semantic Scholar

Social Impact

Altmetric

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

1924

OpenAlex

114

Influential

Cite This

APA Style

                            
                                
                                    Fabien Lotte, 
                                
                                    Laurent Bougrain, 
                                
                                    Andrzej Cichocki
                                
                                et al.
                            
                            (2018). 
                            A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update. 
                            Journal of Neural Engineering
                            , 15
                            (3)
                            , 031005-031005.
                            https://doi.org/10.1088/1741-2552/aab2f2
                        

Identifiers

DOI: 10.1088/1741-2552/aab2f2
PMID: 29488902

Data Quality

Data completeness: 90%