FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing

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Review of challenges associated with the EEG artifact removal methods

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EEG-Informed fMRI: A Review of Data Analysis Methods

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The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

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Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG

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Regulation of arousal via online neurofeedback improves human performance in a demanding sensory-motor task

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Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification

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A Self-Adaptive Online Brain–Machine Interface of a Humanoid Robot Through a General Type-2 Fuzzy Inference System

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Decoding Movement-Related Cortical Potentials Based on Subject-Dependent and Section-Wise Spectral Filtering

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Contact Pressure and Flexibility of Multipin Dry EEG Electrodes

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Heading for new shores! Overcoming pitfalls in BCI design

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Alginate-based hydrogels as an alternative to electrolytic gels for rapid EEG monitoring and easy cleaning procedures

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Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music

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EEG Integrated Platform Lossless (EEG-IP-L) pre-processing pipeline for objective signal quality assessment incorporating data annotation and blind source separation

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Ocular artifact elimination from electroencephalography signals: A systematic review

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Removal of Eye Blink Artifacts From EEG Signals Using Sparsity

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Affective brain–computer music interfacing

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Effects of the road environment on the development of driver sleepiness in young male drivers

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Recent advances and open challenges in hybrid brain-computer interfacing: a technological review of non-invasive human research

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Phase Space Reconstruction of EEG Signals for Classification of ADHD and Control Adults

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Benefits of deep learning classification of continuous noninvasive brain–computer interface control

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Signal Artifacts and Techniques for Artifacts and Noise Removal

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Online EEG artifact removal for BCI applications by adaptive spatial filtering

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A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings

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WeDea: A New EEG-Based Framework for Emotion Recognition

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Applications of Higher Order Statistics in Electroencephalography Signal Processing: A Comprehensive Survey

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Thought-based row-column scanning communication board for individuals with cerebral palsy

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The effect of daylight versus darkness on driver sleepiness: a driving simulator study

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Automated detection of driver fatigue from electroencephalography through wavelet-based connectivity

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Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst

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EEG artifact removal and noise suppression by Discrete Orthonormal S-Transform denoising

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Brain-Computer Interface with Corrupted EEG Data: a Tensor Completion Approach

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Brain–Computer Interface Contributions to Neuroergonomics

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EEG artifacts detection and removal techniques for brain computer interface applications: a systematic review

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Multi-View Multi-Scale Optimization of Feature Representation for EEG Classification Improvement

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The Riemannian Potato Field: A Tool for Online Signal Quality Index of EEG

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Mathematical mindsets increase student motivation: Evidence from the EEG

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Motor Imagery EEG Classification Based on Riemannian Sparse Optimization and Dempster-Shafer Fusion of Multi-Time-Frequency Patterns

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FastEMD–CCA algorithm for unsupervised and fast removal of eyeblink artifacts from electroencephalogram

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The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification

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Minimum Noise Estimate Filter: A Novel Automated Artifacts Removal Method for Field Potentials

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Application of tunable-Q wavelet transform based nonlinear features in epileptic seizure detection

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Ongoing EEG artifact correction using blind source separation

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Filter-Bank Artifact Rejection: High performance real-time single-channel artifact detection for EEG

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A Brief Summary of EEG Artifact Handling

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Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

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Fused Group Lasso: A New EEG Classification Model With Spatial Smooth Constraint for Motor Imagery-Based Brain–Computer Interface

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RNeuMark: A Riemannian EEG Analysis Framework for Neuromarketing

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Preprocessing of EEG

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Pre-Trial EEG-Based Single-Trial Motor Performance Prediction to Enhance Neuroergonomics for a Hand Force Task

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Automated EEG Artifact Handling With Application in Driver Monitoring

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Motor imagery based brain–computer interfaces

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Online denoising of eye-blinks in electroencephalography

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Introducing block-Toeplitz covariance matrices to remaster linear discriminant analysis for event-related potential brain–computer interfaces

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Detection of mental imagery and attempted movements in patients with disorders of consciousness using EEG

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Mental Workload Estimation from EEG Signals Using Machine Learning Algorithms

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Low-complexity hardware design methodology for reliable and automated removal of ocular and muscular artifact from EEG

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EEG-Based Mental Workload Estimation

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Advanced Signal Processing and Machine/Deep Learning Approaches on a Preprocessing Block for EEG Artifact Removal: A Comprehensive Review

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Personalised, Multi-Modal, Affective State Detection for Hybrid Brain-Computer Music Interfacing

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Neural and physiological data from participants listening to affective music

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Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010–2020)

Belkhiria, C., & Peysakhovich, V. (2020) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2020.606719 · Cited by 22

Challenges of neural interfaces for stroke motor rehabilitation

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Identifying music-induced emotions from EEG for use in brain-computer music interfacing

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Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests

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Comparison of a Pragmatic and Regression Approach for Wearable EEG Signal Quality Assessment

Witteveen, J. A., Pradhapan, P., & Mihajlović, V. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2920381 · Cited by 21

EEG Based Decision Support System to Diagnose Adults with ADHD

Kaur, S., Arun, P., Singh, S., & Kaur, D. (2018) · IEEE Applied Signal Processing Conference (ASPCON) · doi:10.1109/aspcon.2018.8748412 · Cited by 20

Reconstruction of missing channel in electroencephalogram using spatiotemporal correlation-based averaging

Bahador, N., Jokelainen, J., Mustola, S. T., & Kortelainen, J. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac23e2 · Cited by 20

Evolving polynomial neural networks for detecting abnormal patterns

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Adaptive Artifact Removal From Intracortical Channels for Accurate Decoding of a Force Signal in Freely Moving Rats

Khorasani, A., Shalchyan, V., & Daliri, M. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00350 · Cited by 19

NeuMa - the absolute Neuromarketing dataset en route to an holistic understanding of consumer behaviour

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Local changes in the wake electroencephalogram precedes lane departures

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Workshops of the eighth international brain–computer interface meeting: BCIs: the next frontier

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Exploration of neural correlates of movement intention based on characterisation of temporal dependencies in electroencephalography

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Game-Based BCI Training: Interactive Design for Individuals with Cerebral Palsy

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Removal of ocular artifacts from multichannel EEG signal using wavelet enhanced ICA

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Application of hybrid GLCT-PICA de-noising method in automated EEG artifact removal

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Handling EEG artifacts and searching individually optimal experimental parameter in real time: a system development and demonstration

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A Review on EEG Artifacts And Its Different Removal Technique

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Direct comparison of supervised and semi-supervised retraining approaches for co-adaptive BCIs

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An Unsupervised Method for Artefact Removal in EEG Signals

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Performance Comparison of Automated EEG Enhancement Algorithms for Mental Workload Assessment of Ambulant Users

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Objective selection of epilepsy-related independent components from EEG data

Abreu, R., Leite, M., Leal, A., & Figueiredo, P. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.10.003 · Cited by 13

Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

Mur, A., Dormido, R., Vega, J., Duro, N., & Dormido-Canto, S. (2016) · Sensors · doi:10.3390/s16040590 · Cited by 13

Lets play Tic-Tac-Toe: A Brain-Computer Interface case study in cerebral palsy

Scherer, R., Schwarz, A., Muller-Putz, G. R., Pammer‐Schindler, V., & García, M. L. (2016) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2016.7844815 · Cited by 12

Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry

Georgiadis, K., Kalaganis, F. P., Oikonomou, V. P., Nikolopoulos, S., Laskaris, N., & Kompatsiaris, I. Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43075-6_3 · Cited by 11

Online detection and removal of eye blink artifacts from electroencephalogram

Egambaram, A., Badruddin, N., Asirvadam, V. S., Begum, T., Fauvet, É., & Stolz, C. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102887 · Cited by 11

EEG artifact correction strategies for online trial-by-trial analysis

de Freitas, A. M., Sanchez, G., Lecaignard, F., Maby, E., Soares, A. B., & Mattout, J. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab581d · Cited by 13

Classification of motor imagery EEG signals based on wavelet transform and sample entropy

Ma, M., Guo, L., Su, K., & Liang, D. (2017) · IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) · doi:10.1109/iaeac.2017.8054145 · Cited by 10

Cepstral Analysis-Based Artifact Detection, Recognition, and Removal for Prefrontal EEG

Han, S., Zhang, C., Lei, J., Han, Q., Du, Y., Wang, A., Bai, S., & Zhang, M. (2023) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2023.3266594 · Cited by 9

A Learnable and Explainable Wavelet Neural Network for EEG Artifacts Detection and Classification

Yu, Y., Li, Y., Zhou, Y., Wang, Y., & Wang, J. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3452315 · Cited by 9

Adaptive filtering in EEG Signal for Artifacts Removal using Learning Algorithm

(2019) · Journal of Networking and Communication Systems (JNACS) · doi:10.46253/jnacs.v2i2.a1 · Cited by 9

Artifacts characterization and removal in EEG brain-computer interface

Ren, S. H. (2016) · DR-NTU (Nanyang Technological University)

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

Zhang, C., Li, T., Zeng, Y., Jiang, J., Bu, H., Yan, B., & Li, J. (2015) · BioMed Research International · doi:10.1155/2015/720450 · Cited by 40

Online artifact removal in EEG signals

Matsusaki, F., Ikuno, T., Katayama, Y., & Iramina, K. (2013) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-642-29305-4_94 · Cited by 4

Automatic artefact removal in a self-paced hybrid brain- computer interface system

Yong, X., Fatourechi, M., Ward, R. K., & Birch, G. E. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-50 · Cited by 33

Artifact Removal of EEG Signals for Brain Computer Interface

Verma, A., Anand, R. S., & Sharma, A. (2010) · doi:10.13140/rg.2.2.23231.38563