Brain-Computer Interfaces

Aims & Scope

Brain-Computer Interfaces ( BCI) publishes high quality, original research articles encompassing analysis of theoretical and practical advances in brain-computer interface (BCI) technology.

Articles should expand upon novel and innovative research where the methods, analysis and conclusions are robust and of the highest standard.

A BCI measures brain activity and translates it into a form that can allow machines to compensate for lost or damaged brain functions, provide supplementary or augmented functions, or entrain lasting improvements in existing functions.

The Journal recognizes that the field of BCI research is highly multi-disciplinary, and strives to integrate a range of perspectives from various disciplines in order to deepen understanding of the issues, challenges and solutions in the field.

Brain-Computer Interfaces will be of interest to experts within the following fields: neuroscience - biomedical engineering - neurosurgery - rehabilitation engineering - psychology - human factors - computer science and engineering - machine learning - electrical engineering - industrial and systems engineering - mechanical engineering.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.1
2024	1.80

Journal Rank

Year	Value
2024	11970

Journal Citation Indicator

Year	Value
2024	81

SJR (SCImago Journal Rank)

Year	Value
2024	0.480

Quartile

Year	Value
2024	Q2

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Engineering and Neuroscience, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review

  Citation: 352

  Authors: Marco, Alexandre, Rajendra

• A high-ITR SSVEP-based BCI speller

  Citation: 256

  Authors: Xiaogang, Zhikai, Shangkai, Xiaorong

• A survey of affective brain computer interfaces: principles, state-of-the-art, and challenges

  Citation: 221

  Authors: Christian, Brendan, Anton, Guillaume

• BNCI Horizon 2020: towards a roadmap for the BCI community

  Citation: 179

  Authors: Clemens, Niels, Benjamin, Christoph, Andrea, Donatella, José del R., Felip, Anton, Eloy, Nick, Patric, Gernot R.

• Brain-computer interface-based control of closed-loop brain stimulation: attitudes and ethical considerations

  Citation: 120

  Authors: Eran, Sara, Josh, Conor V., Rachel, Samuel, Darin D., Alik S.

• EEG-based classification of positive and negative affective states

  Citation: 90

  Authors: Maja, Robin R., Veasna, Chris

• Heading for new shores! Overcoming pitfalls in BCI design

  Citation: 76

  Authors: Ricardo, Melanie, Sonja, Fabien, Reinhold

• Therapeutic applications of BCI technologies

  Citation: 56

  Authors: Dennis J., Janis, Chadwick, Muhammad A.

• Brain Painting V2: evaluation of P300-based brain-computer interface for creative expression by an end-user following the user-centered design

  Citation: 53

  Authors: L., E.M., A.

• Recent advances and open challenges in hybrid brain-computer interfacing: a technological review of non-invasive human research

  Citation: 51

  Authors: H., T.H.

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