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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 interfaces in neurorehabilitation of stroke
Surjo R. Soekadar, Niels Birbaumer, Marc W. Slutzky, et al.
Neurobiology of Disease (2014) Vol. 83, pp. 172-179
Open Access | Times Cited: 306

Showing 1-25 of 306 citing articles:

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
Erico Tjoa, Cuntai Guan
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 11, pp. 4793-4813
Open Access | Times Cited: 1410
Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery
Samar M. Hatem, Geoffroy Saussez, Margaux della Faille, et al.
Frontiers in Human Neuroscience (2016) Vol. 10
Open Access | Times Cited: 768
Brain–computer interface boosts motor imagery practice during stroke recovery
Floriana Pichiorri, Giovanni Morone, Manuela Petti, et al.
Annals of Neurology (2015) Vol. 77, Iss. 5, pp. 851-865
Open Access | Times Cited: 566
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation
Mikhail Lebedev, Miguel A. L. Nicolelis
Physiological Reviews (2017) Vol. 97, Iss. 2, pp. 767-837
Closed Access | Times Cited: 550
Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial
Alexander Frolov, О. А. Мокиенко, R. Kh. Lyukmanov, et al.
Frontiers in Neuroscience (2017) Vol. 11
Open Access | Times Cited: 321
BCI for stroke rehabilitation: motor and beyond
Ravikiran Mane, Tushar Chouhan, Cuntai Guan
Journal of Neural Engineering (2020) Vol. 17, Iss. 4, pp. 041001-041001
Open Access | Times Cited: 313
EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications
Xiaotong Gu, Zehong Cao, Alireza Jolfaei, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 18, Iss. 5, pp. 1645-1666
Open Access | Times Cited: 273
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Xiang Zhang, Lina Yao, Xianzhi Wang, et al.
Journal of Neural Engineering (2020) Vol. 18, Iss. 3, pp. 031002-031002
Open Access | Times Cited: 228
Hybrid EEG/EOG-based brain/neural hand exoskeleton restores fully independent daily living activities after quadriplegia
Surjo R. Soekadar, Matthias Witkowski, Cristina Gómez, et al.
Science Robotics (2016) Vol. 1, Iss. 1
Closed Access | Times Cited: 205
The Berlin Brain-Computer Interface: Progress Beyond Communication and Control
Benjamin Blankertz, Laura Acqualagna, Sven Dähne, et al.
Frontiers in Neuroscience (2016) Vol. 10
Open Access | Times Cited: 198
New neural activity patterns emerge with long-term learning
Emily R. Oby, Matthew D. Golub, Jay A. Hennig, et al.
Proceedings of the National Academy of Sciences (2019) Vol. 116, Iss. 30, pp. 15210-15215
Open Access | Times Cited: 192
Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application
Muhammad Ahmed Khan, Rig Das, Helle K. Iversen, et al.
Computers in Biology and Medicine (2020) Vol. 123, pp. 103843-103843
Open Access | Times Cited: 187
Role of the Contralesional vs. Ipsilesional Hemisphere in Stroke Recovery
Keith Dodd, Veena A. Nair, Vivek Prabhakaran
Frontiers in Human Neuroscience (2017) Vol. 11
Open Access | Times Cited: 185
Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke
Martina Coscia, Maximilian J. Wessel, Ujwal Chaudary, et al.
Brain (2019) Vol. 142, Iss. 8, pp. 2182-2197
Open Access | Times Cited: 179
Wireless EEG: A survey of systems and studies
Guiomar Niso, Elena Romero, Jeremy T. Moreau, et al.
NeuroImage (2022) Vol. 269, pp. 119774-119774
Open Access | Times Cited: 123
Mapping entrained brain oscillations during transcranial alternating current stimulation (tACS)
Matthias Witkowski, Eliana García‐Cossio, Bankim Subhash Chander, et al.
NeuroImage (2015) Vol. 140, pp. 89-98
Closed Access | Times Cited: 174
Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation
Max Krucoff, Shervin Rahimpour, Marc W. Slutzky, et al.
Frontiers in Neuroscience (2016) Vol. 10
Open Access | Times Cited: 162
Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors
Nikunj Bhagat, Anusha Venkatakrishnan, Berdakh Abibullaev, et al.
Frontiers in Neuroscience (2016) Vol. 10
Open Access | Times Cited: 156
Fully portable and wireless universal brain–machine interfaces enabled by flexible scalp electronics and deep learning algorithm
Musa Mahmood, Deogratias Mzurikwao, Yun‐Soung Kim, et al.
Nature Machine Intelligence (2019) Vol. 1, Iss. 9, pp. 412-422
Closed Access | Times Cited: 142
Effects of a Brain-Computer Interface With Virtual Reality (VR) Neurofeedback: A Pilot Study in Chronic Stroke Patients
Athanasios Vourvopoulos, Octavio Marin Pardo, Stéphanie Lefebvre, et al.
Frontiers in Human Neuroscience (2019) Vol. 13
Open Access | Times Cited: 125
A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke
Alexander Remsik, Brittany M. Young, Rebecca Vermilyea, et al.
Expert Review of Medical Devices (2016) Vol. 13, Iss. 5, pp. 445-454
Open Access | Times Cited: 123
A Systematic Review Establishing the Current State-of-the-Art, the Limitations, and the DESIRED Checklist in Studies of Direct Neural Interfacing With Robotic Gait Devices in Stroke Rehabilitation
Olive Lennon, Michele Tonellato, Alessandra Del Felice, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 123
Flexible Graphene Solution‐Gated Field‐Effect Transistors: Efficient Transducers for Micro‐Electrocorticography
Clément Hébert, Eduard Masvidal‐Codina, Alejandro Suarez‐Perez, et al.
Advanced Functional Materials (2017) Vol. 28, Iss. 12
Open Access | Times Cited: 115
Improving Motor Corticothalamic Communication After Stroke Using Real-Time fMRI Connectivity-Based Neurofeedback
Sook-Lei Liew, Mohit Rana, Sonja Cornelsen, et al.
Neurorehabilitation and neural repair (2015) Vol. 30, Iss. 7, pp. 671-675
Open Access | Times Cited: 106
Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects
Camille Jeunet, Bertrand Glize, Aileen McGonigal, et al.
Neurophysiologie Clinique (2018) Vol. 49, Iss. 2, pp. 125-136
Open Access | Times Cited: 95
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