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:

Brain–Computer Interfaces Using Sensorimotor Rhythms: Current State and Future Perspectives
Han Yuan, Bin He
IEEE Transactions on Biomedical Engineering (2014) Vol. 61, Iss. 5, pp. 1425-1435
Open Access | Times Cited: 433

Showing 1-25 of 433 citing articles:

A comprehensive review of EEG-based brain–computer interface paradigms
Reza Abiri, Soheil Borhani, Eric W. Sellers, et al.
Journal of Neural Engineering (2018) Vol. 16, Iss. 1, pp. 011001-011001
Closed Access | Times Cited: 753

A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines
Na Lu, Tengfei Li, Xiaodong Ren, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2016) Vol. 25, Iss. 6, pp. 566-576
Closed Access | Times Cited: 412

EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks
Bradley J. Edelman, Bryan Baxter, Bin He
IEEE Transactions on Biomedical Engineering (2015) Vol. 63, Iss. 1, pp. 4-14
Open Access | Times Cited: 335

Quo vadis artificial intelligence?
Yuchen Jiang, Xiang Li, Hao Luo, et al.
Discover Artificial Intelligence (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 312

Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI
Yu Zhang, Chang S. Nam, Guoxu Zhou, et al.
IEEE Transactions on Cybernetics (2018) Vol. 49, Iss. 9, pp. 3322-3332
Open Access | Times Cited: 300

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

EEG-based brain–computer interfaces
Dennis J. McFarland, Jonathan R. Wolpaw
Current Opinion in Biomedical Engineering (2017) Vol. 4, pp. 194-200
Open Access | Times Cited: 228

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

Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms
Bin He, Bryan Baxter, Bradley J. Edelman, et al.
Proceedings of the IEEE (2015) Vol. 103, Iss. 6, pp. 907-925
Open Access | Times Cited: 207

Interface, interaction, and intelligence in generalized brain–computer interfaces
Xiaorong Gao, Yijun Wang, Xiaogang Chen, et al.
Trends in Cognitive Sciences (2021) Vol. 25, Iss. 8, pp. 671-684
Closed Access | Times Cited: 175

A novel hybrid deep learning scheme for four-class motor imagery classification
Ruilong Zhang, Qun Zong, Liqian Dou, et al.
Journal of Neural Engineering (2019) Vol. 16, Iss. 6, pp. 066004-066004
Closed Access | Times Cited: 159

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

Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks
Ji-Seon Bang, Min-Ho Lee, Siamac Fazli, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 7, pp. 3038-3049
Closed Access | Times Cited: 130

Brain-computer interface for hands-free teleoperation of construction robots
Yizhi Liu, Mahmoud Habibnezhad, Houtan Jebelli
Automation in Construction (2021) Vol. 123, pp. 103523-103523
Closed Access | Times Cited: 112

Brain–computer interfaces
Jonathan R. Wolpaw
Handbook of clinical neurology (2013), pp. 67-74
Closed Access | Times Cited: 174

Separable Common Spatio-Spectral Patterns for Motor Imagery BCI Systems
Amirhossein S. Aghaei, Mohammad Shahin Mahanta, Konstantinos N. Plataniotis
IEEE Transactions on Biomedical Engineering (2015) Vol. 63, Iss. 1, pp. 15-29
Closed Access | Times Cited: 155

Towards correlation-based time window selection method for motor imagery BCIs
Jiankui Feng, Erwei Yin, Jing Jin, et al.
Neural Networks (2018) Vol. 102, pp. 87-95
Open Access | Times Cited: 140

MOABB: trustworthy algorithm benchmarking for BCIs
Vinay Jayaram, Alexandre Barachant
Journal of Neural Engineering (2018) Vol. 15, Iss. 6, pp. 066011-066011
Open Access | Times Cited: 139

Brain-Computer Interface Control in a Virtual Reality Environment and Applications for the Internet of Things
Christopher Coogan, Bin He
IEEE Access (2018) Vol. 6, pp. 10840-10849
Open Access | Times Cited: 138

Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
Lucia Rita Quitadamo, Francesco Cavrini, Laura Sbernini, et al.
Journal of Neural Engineering (2017) Vol. 14, Iss. 1, pp. 011001-011001
Open Access | Times Cited: 119

Decoding hand gestures from primary somatosensory cortex using high-density ECoG
Mariana P. Branco, Zachary V. Freudenburg, Erik J. Aarnoutse, et al.
NeuroImage (2016) Vol. 147, pp. 130-142
Open Access | Times Cited: 118

Enhanced Motor Imagery Training Using a Hybrid BCI With Feedback
Tianyou Yu, Jun Xiao, Fangyi Wang, et al.
IEEE Transactions on Biomedical Engineering (2015) Vol. 62, Iss. 7, pp. 1706-1717
Closed Access | Times Cited: 114

Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network
Kai Zhang, Guanghua Xu, Zezhen Han, et al.
Sensors (2020) Vol. 20, Iss. 16, pp. 4485-4485
Open Access | Times Cited: 99

A Multi-Scale Fusion Convolutional Neural Network Based on Attention Mechanism for the Visualization Analysis of EEG Signals Decoding
Donglin Li, Jiacan Xu, Jianhui Wang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 12, pp. 2615-2626
Closed Access | Times Cited: 94

Brain–Computer Interfaces
Bin He, Han Yuan, Jianjun Meng, et al.
Springer eBooks (2020), pp. 131-183
Closed Access | Times Cited: 94

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