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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:

Brain–Machine Interface-Driven Post-Stroke Upper-Limb Functional Recovery Correlates With Beta-Band Mediated Cortical Networks
Dheeraj Rathee, Anirban Chowdhury, Yogesh Kumar Meena, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 27, Iss. 5, pp. 1020-1031
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis
Zhongfei Bai, Kenneth N. K. Fong, Jiaqi Zhang, et al.
Journal of NeuroEngineering and Rehabilitation (2020) Vol. 17, Iss. 1
Open Access | Times Cited: 157
Brain–computer interface robotics for hand rehabilitation after stroke: a systematic review
Paul Dominick E. Baniqued, Emily C. Stanyer, Muhammad Awais, et al.
Journal of NeuroEngineering and Rehabilitation (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 152
Diamond quantum magnetometer with dc sensitivity of sub-10 pT Hz−1/2 toward measurement of biomagnetic field
Naota Sekiguchi, Motofumi Fushimi, Akihiko Yoshimura, et al.
Physical Review Applied (2024) Vol. 21, Iss. 6
Open Access | Times Cited: 10
Motor Imagery Hand Movement Direction Decoding Using Brain Computer Interface to Aid Stroke Recovery and Rehabilitation
V. K. Benzy, A. P. Vinod, R Subasree, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 12, pp. 3051-3062
Closed Access | Times Cited: 66
Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation
Nikunj Bhagat, Nuray Yozbatıran, Jennifer L. Sullivan, et al.
NeuroImage Clinical (2020) Vol. 28, pp. 102502-102502
Open Access | Times Cited: 45
Deep Learning based Prediction of EEG Motor Imagery of Stroke Patients’ for Neuro-Rehabilitation Application
Haider Raza, Anirban Chowdhury, Saugat Bhattacharyya
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-8
Open Access | Times Cited: 39
Towards a mechanistic approach for the development of non‐invasive brain‐computer interfaces for motor rehabilitation
Natalie Mrachacz‐Kersting, Jaime Ibáñez, Dario Farina
The Journal of Physiology (2021) Vol. 599, Iss. 9, pp. 2361-2374
Open Access | Times Cited: 32
Action observation training and brain-computer interface controlled functional electrical stimulation enhance upper extremity performance and cortical activation in patients with stroke: a randomized controlled trial
S. Lee, Seong-Sik Kim, Byoung‐Hee Lee
Physiotherapy Theory and Practice (2020) Vol. 38, Iss. 9, pp. 1126-1134
Closed Access | Times Cited: 33
EEG characteristic investigation of the sixth-finger motor imagery and optimal channel selection for classification
Yuan Liu, Zhuang Wang, Shuaifei Huang, et al.
Journal of Neural Engineering (2022) Vol. 19, Iss. 1, pp. 016001-016001
Closed Access | Times Cited: 20
Assessing impact of channel selection on decoding of motor and cognitive imagery from MEG data
Sujit Roy, Dheeraj Rathee, Anirban Chowdhury, et al.
Journal of Neural Engineering (2020) Vol. 17, Iss. 5, pp. 056037-056037
Open Access | Times Cited: 28
A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface
Dheeraj Rathee, Haider Raza, Sujit Roy, et al.
Scientific Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 25
The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia
Shugeng Chen, Xiaokang Shu, Hewei Wang, et al.
Frontiers in Neurorobotics (2021) Vol. 15
Open Access | Times Cited: 25
Transfer Learning Based on Optimal Transport for Motor Imagery Brain-Computer Interfaces
Victoria Peterson, Nicolás Nieto, Dominik Wyser, et al.
IEEE Transactions on Biomedical Engineering (2021) Vol. 69, Iss. 2, pp. 807-817
Closed Access | Times Cited: 24
The role of brain oscillations in post-stroke motor recovery: An overview
Giulia C. Leonardi, Rosella Ciurleo, Francesca Cucinotta, et al.
Frontiers in Systems Neuroscience (2022) Vol. 16
Open Access | Times Cited: 18
Motor Impairment in Stroke Patients Is Associated With Network Properties During Consecutive Motor Imagery
Minji Lee, Yun‐Hee Kim, Seong‐Whan Lee
IEEE Transactions on Biomedical Engineering (2022) Vol. 69, Iss. 8, pp. 2604-2615
Closed Access | Times Cited: 17
Neural Interface-Based Motor Neuroprosthesis in Poststroke Upper Limb Neurorehabilitation: An Individual Patient Data Meta-analysis
Yu Tung Lo, Mervyn Jun Rui Lim, Chun Yen Kok, et al.
Archives of Physical Medicine and Rehabilitation (2024)
Open Access | Times Cited: 3
The clinical effects of brain–computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review
Hao Qu, Feixiang Zeng, Yongbin Tang, et al.
Disability and Rehabilitation Assistive Technology (2022) Vol. 19, Iss. 1, pp. 30-41
Closed Access | Times Cited: 14
Clinical Brain–Computer Interface Challenge 2020 (CBCIC at WCCI2020): Overview, Methods and Results
Anirban Chowdhury, Javier Andreu-Pérez
IEEE Transactions on Medical Robotics and Bionics (2021) Vol. 3, Iss. 3, pp. 661-670
Open Access | Times Cited: 18
Rehabilitation Modulates High-Order Interactions Among Large-Scale Brain Networks in Subacute Stroke
Ileana Pirovano, Yuri Antonacci, Alfonso Mastropietro, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 4549-4560
Open Access | Times Cited: 5
The Influence of Visual Attention on The Performance of A Novel Tactile P300 Brain-Computer Interface with Cheeks-Stim Paradigm
Ying Mao, Jing Jin, Ren Xu, et al.
International Journal of Neural Systems (2020) Vol. 31, Iss. 04, pp. 2150004-2150004
Closed Access | Times Cited: 13
Analysis of brain network differences in the active, motor imagery, and passive stoke rehabilitation paradigms based on the task-state EEG
Haolong Su, Gege Zhan, Yifang Lin, et al.
Brain Research (2024) Vol. 1846, pp. 149261-149261
Closed Access | Times Cited: 1
Finger-Individuating Exoskeleton System with Non-Contact Leader–Follower Control Strategy
Zhenyu Sun, Xiaobei Jing, Xinyu Zhang, et al.
Bioengineering (2024) Vol. 11, Iss. 8, pp. 754-754
Open Access | Times Cited: 1
Neural Decoding of Chinese Sign Language With Machine Learning for Brain–Computer Interfaces
Pengpai Wang, Yueying Zhou, Zhongnian Li, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 2721-2732
Open Access | Times Cited: 9
Relationship between resting-state functional connectivity and change in motor function after motor imagery intervention in patients with stroke: a scoping review
Kenya Tanamachi, Wataru Kuwahara, Megumi Okawada, et al.
Journal of NeuroEngineering and Rehabilitation (2023) Vol. 20, Iss. 1
Open Access | Times Cited: 2
Can Corticomuscular Coupling be Useful in Designing Hybrid-Brain Robot Interfaces Towards Hand Functional Recovery?
Anirban Chowdhury, Ashish Dutta, Girijesh Prasad
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2019)
Open Access | Times Cited: 4
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