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

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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

Meinel, A., Castaño-Candamil, S., Reis, J., & Tangermann, M. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00170 · Cited by 28 · see citing works

Automated EEG Artifact Handling With Application in Driver Monitoring

Barua, S., Ahmed, M. U., Ahlstrom, C. H. G., Begum, S., & Funk, P. J. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2773999 · Cited by 28 · see citing works

Motor imagery based brain–computer interfaces

Scherer, R., & Vidaurre, C. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812892-3.00008-x · Cited by 29 · see citing works

Online denoising of eye-blinks in electroencephalography

Barthélemy, Q., Mayaud, L., Renard, Y., Kim, D., Kang, S., Gunkelman, J. D., & Congedo, M. (2017) · Neurophysiologie Clinique · doi:10.1016/j.neucli.2017.10.059 · Cited by 26 · see citing works

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

Sosulski, J., & Tangermann, M. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac9c98 · Cited by 26 · see citing works

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

Horki, P., Bauernfeind, G., Klobassa, D. S., Pokorny, C., Pichler, G., Schippinger, W., & Muller-Putz, G. R. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01009 · Cited by 25 · see citing works

Mental Workload Estimation from EEG Signals Using Machine Learning Algorithms

Cheema, B. S., Samima, S., Sarma, M., & Samanta, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91122-9_23 · Cited by 25 · see citing works

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

Acharyya, A., Jadhav, P., Bono, V., Maharatna, K., & Naik, G. R. (2018) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2018.02.009 · Cited by 25 · see citing works

EEG-Based Mental Workload Estimation

Samima, S., & Sarma, M. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857164 · Cited by 25 · see citing works

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

Agounad, S., Tarahi, O., Moufassih, M., Hamou, S., & Mazid, A. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02936-3 · Cited by 23 · see citing works

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

Daly, I. P., Williams, D. A. H., Malik, A., Weaver, J., Kirke, A., Hwang, F., Miranda, E. R., & Nasuto, S. J. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2801811 · Cited by 23 · see citing works

Neural and physiological data from participants listening to affective music

Daly, I. P., Nicolaou, N., Williams, D. A. H., Hwang, F., Kirke, A., Miranda, E. R., & Nasuto, S. J. (2020) · Scientific Data · doi:10.1038/s41597-020-0507-6 · Cited by 23 · see citing works

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 · see citing works

Challenges of neural interfaces for stroke motor rehabilitation

Vidaurre, C., Irastorza-Landa, N., Sarasola-Sanz, A., Insausti-Delgado, A., Ray, A. M., Bibián, C., Helmhold, F., Mahmoud, W. J., Ortego-Isasa, I., López‐Larraz, E., et al. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1070404 · Cited by 21 · see citing works

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

Daly, I. P., Malik, A., Weaver, J., Hwang, F., Nasuto, S. J., Williams, D. A. H., Kirke, A., & Miranda, E. R. (2015) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2015.7344685 · Cited by 22 · see citing works

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

Anastasiadou, M. N., Christodoulakis, M., Papathanasiou, E. S., Papacostas, S., & Mitsis, G. D. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.06.247 · Cited by 22 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

Evolving polynomial neural networks for detecting abnormal patterns

Nyah, N., Jakaite, L., Schetinin, V., Sant, P., & Aggoun, A. (2016) · IEEE International Conference on Intelligent Systems · doi:10.1109/is.2016.7737403 · Cited by 19 · see citing works

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 · see citing works

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

Georgiadis, K., Kalaganis, F. P., Riskos, K., Matta, E., Oikonomou, V., Yfantidou, I., Chantziaras, D., Pantouvakis, K., Nikolopoulos, S., Laskaris, N. A., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02392-9 · Cited by 19 · see citing works

Local changes in the wake electroencephalogram precedes lane departures

Ahlstrom, C. H. G., Jansson, S., & Anund, A. (2017) · Journal of Sleep Research · doi:10.1111/jsr.12527 · Cited by 17 · see citing works

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

Huggins, J. E., Krusienski, D. J., Vansteensel, M. J., Valeriani, D., Thelen, A., Stavisky, S. D., Norton, J. J. S., Nijholt, A., Muller-Putz, G. R., Kosmyna, N., et al. (2022) · Brain-Computer Interfaces · doi:10.1080/2326263x.2021.2009654 · Cited by 17 · see citing works

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

Wairagkar, M., Hayashi, Y., & Nasuto, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0193722 · Cited by 14 · see citing works

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

Scherer, R., Schwarz, A., Muller-Putz, G. R., Pammer‐Schindler, V., & García, M. L. (2015) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2015.551 · Cited by 17 · see citing works

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

Paradeshi, K. P., Scholar, R., & Kolekar, U. D. (2017) · International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) · doi:10.1109/icecds.2017.8390150 · Cited by 15 · see citing works

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

Jindal, K., Upadhyay, R., & Singh, H. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101977 · Cited by 15 · see citing works

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

Ouyang, G., Dien, J., & Lorenz, R. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac42b6 · Cited by 15 · see citing works

A Review on EEG Artifacts And Its Different Removal Technique

Jung, C. Y. (2016) · Asia-pacific Journal of Convergent Research Interchange · doi:10.21742/apjcri.2016.12.06 · Cited by 15 · see citing works

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

Schwarz, A., Brandstetter, J., Pereira, J., & Muller-Putz, G. R. (2019) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-019-02047-1 · Cited by 15 · see citing works

An Unsupervised Method for Artefact Removal in EEG Signals

Mur, A., Dormido, R., & Duro, N. (2019) · Sensors · doi:10.3390/s19102302 · Cited by 14 · see citing works

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

Rosanne, O., Albuquerque, I., Gagnon, J.-F., Tremblay, S., & Falk, T. H. (2019) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2019.8716977 · Cited by 14 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 11 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 31 · see citing works

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