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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Towards a Cure for BCI Illiteracy
Carmen Vidaurre, Benjamin Blankertz
Brain Topography (2009) Vol. 23, Iss. 2, pp. 194-198
Open Access | Times Cited: 452

Showing 1-25 of 452 citing articles:

Single-trial analysis and classification of ERP components — A tutorial
Benjamin Blankertz, Steven Lemm, Matthias S. Treder, et al.
NeuroImage (2010) Vol. 56, Iss. 2, pp. 814-825
Closed Access | Times Cited: 1073
Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges
José del R. Millán, Rüdiger Rupp, Gernot Müller-Putz, et al.
Frontiers in Neuroscience (2010) Vol. 1
Open Access | Times Cited: 818
Towards the utilization of EEG as a brain imaging tool
Christoph M. Michel, Micah M. Murray
NeuroImage (2011) Vol. 61, Iss. 2, pp. 371-385
Closed Access | Times Cited: 640
Introduction to machine learning for brain imaging
Steven Lemm, Benjamin Blankertz, Thorsten Dickhaus, et al.
NeuroImage (2010) Vol. 56, Iss. 2, pp. 387-399
Closed Access | Times Cited: 614
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
Natasha Padfield, Jaime Zabalza, Huimin Zhao, et al.
Sensors (2019) Vol. 19, Iss. 6, pp. 1423-1423
Open Access | Times Cited: 469
EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy
Min-Ho Lee, Oyeon Kwon, Yong-Jeong Kim, et al.
GigaScience (2019) Vol. 8, Iss. 5
Open Access | Times Cited: 390
The Berlin Brain–Computer Interface: Non-Medical Uses of BCI Technology
Benjamin Blankertz, Michael Tangermann, Carmen Vidaurre, et al.
Frontiers in Neuroscience (2010) Vol. 4
Open Access | Times Cited: 335
Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface
Muhammad Jawad Khan, Melissa Jiyoun Hong, Keum‐Shik Hong
Frontiers in Human Neuroscience (2014) Vol. 8
Open Access | Times Cited: 274
Trends in EEG-BCI for daily-life: Requirements for artifact removal
Jesús Minguillón, M. A. López-Gordo, Francisco Pelayo
Biomedical Signal Processing and Control (2016) Vol. 31, pp. 407-418
Closed Access | Times Cited: 264
Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI
Fatemeh Fahimi, Zhuo Zhang, Wooi Boon Goh, et al.
Journal of Neural Engineering (2018) Vol. 16, Iss. 2, pp. 026007-026007
Open Access | Times Cited: 225
EEG-Based Strategies to Detect Motor Imagery for Control and Rehabilitation
Kai Keng Ang, Cuntai Guan
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2016) Vol. 25, Iss. 4, pp. 392-401
Closed Access | Times Cited: 223
Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control
Muhammad Jawad Khan, Keum‐Shik Hong
Frontiers in Neurorobotics (2017) Vol. 11
Open Access | Times Cited: 210
Open Access Dataset for EEG+NIRS Single-Trial Classification
Jaeyoung Shin, Alexander von Lühmann, Benjamin Blankertz, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2016) Vol. 25, Iss. 10, pp. 1735-1745
Closed Access | Times Cited: 202
A Brain–Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli
Minpeng Xu, Xiaolin Xiao, Yijun Wang, et al.
IEEE Transactions on Biomedical Engineering (2018) Vol. 65, Iss. 5, pp. 1166-1175
Closed Access | Times Cited: 201
Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review
Simanto Saha, Mathias Baumert
Frontiers in Computational Neuroscience (2020) Vol. 13
Open Access | Times Cited: 201
Brain–machine interfaces for controlling lower-limb powered robotic systems
Yongtian He, David Eguren, José M. Azorín, et al.
Journal of Neural Engineering (2018) Vol. 15, Iss. 2, pp. 021004-021004
Open Access | Times Cited: 200
Consumer grade EEG devices: are they usable for control tasks?
Rytis Maskeliūnas, Robertas Damaševičius, Ignas Martišius, et al.
PeerJ (2016) Vol. 4, pp. e1746-e1746
Open Access | Times Cited: 184
Sparse Group Representation Model for Motor Imagery EEG Classification
Yong Jiao, Yu Zhang, Xun Chen, et al.
IEEE Journal of Biomedical and Health Informatics (2018) Vol. 23, Iss. 2, pp. 631-641
Closed Access | Times Cited: 176
Assessment of the Efficacy of EEG-Based MI-BCI With Visual Feedback and EEG Correlates of Mental Fatigue for Upper-Limb Stroke Rehabilitation
Ruyi Foong, Kai Keng Ang, Chai Quek, et al.
IEEE Transactions on Biomedical Engineering (2019) Vol. 67, Iss. 3, pp. 786-795
Closed Access | Times Cited: 161
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Alexander E. Hramov, Vladimir Maksimenko, Alexander N. Pisarchik
Physics Reports (2021) Vol. 918, pp. 1-133
Closed Access | Times Cited: 153
Review of Machine Learning Techniques for EEG Based Brain Computer Interface
Swati Aggarwal, Nupur Chugh
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 5, pp. 3001-3020
Closed Access | Times Cited: 148
BENDR: Using Transformers and a Contrastive Self-Supervised Learning Task to Learn From Massive Amounts of EEG Data
Demetres Kostas, Stéphane Aroca-Ouellette, Frank Rudzicz
Frontiers in Human Neuroscience (2021) Vol. 15
Open Access | Times Cited: 138
Real-time EEG feedback during simultaneous EEG–fMRI identifies the cortical signature of motor imagery
Catharina Zich, Stefan Debener, Cornelia Kranczioch, et al.
NeuroImage (2015) Vol. 114, pp. 438-447
Closed Access | Times Cited: 169
BCI Demographics II: How Many (and What Kinds of) People Can Use a High-Frequency SSVEP BCI?
Ivan Volosyak, Diana Valbuena, Thorsten Lüth, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2011) Vol. 19, Iss. 3, pp. 232-239
Closed Access | Times Cited: 167
EEG-based BCI and video games: a progress report
Bojan Kerouš, Filip Škola, Fotis Liarokapis
Virtual Reality (2017) Vol. 22, Iss. 2, pp. 119-135
Closed Access | Times Cited: 167
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