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Bibliometric analysis on Brain-computer interfaces in a 30-year period

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Abstract

Brain-computer interfaces (BCIs), as a promising technology for rehabilitation, have attracted significant interest in the fields such as neurosciences, computer science, and biomedical engineering. Based on the expanded database of Science Citation Index, this paper analyzes bibliometrics in the field of BCI from 1990 to 2020 and discusses its potential research trends and prospects. The work provides a detailed overview of the BCI research status founded on the country, research area, institution, journal, author, citation, and keyword. A total of 7,880 papers suggest that the United States is leading the field of BCI research, followed by China and Germany. University of California system has produced the most publications, while the Graz University of Technology is leading the list for the h-index. Journal of Neural Engineering and IEEE Transactions on Neural Systems and Rehabilitation Engineering were identified to be the most productive journals in BCIs. Keywords analysis reflects that most research has focused on electroencephalography (EEG)-based BCIs to achieve a safe, real-time, stable link between the patient and artificial actuators. We can conclude by analyzing hot articles that new materials applied to neural probes may become the next hot topic. The typical paradigm of the BCI industry is the most urgent problem that can be solved in the standardization process. The rehabilitation applications appear as the initial driving force and ultimate goal for BCIs. This research can offer valuable references to BCI practitioners and provide data support for related studies.

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Materials Availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

Code Availability

availability: Code sharing not applicable to this article as no code were generated or analysed during the current study.

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Funding

This research was funded by the Natural Science Foundation of China (Grand Nos. 52175124, 51775501), the Zhejiang Provincial Natural Science Foundation (Grant No. LZ21E050003), and the Fundamental Research Funds for the Zhejiang Provincial Universities (Grant No. RF-C2020004).

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Authors and Affiliations

  1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310013, Zhejiang, People’s Republic of China

    Zichao Yin, Lin Li, Tong Wang, Zheng Wang & Dapeng Tan

  2. Institute of Information Resource, Zhejiang University of Technology, Hangzhou, 310013, Zhejiang, People’s Republic of China

    Yuehua Wan & Hui Fang

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  1. Zichao Yin
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  4. Lin Li
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  5. Tong Wang
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  6. Zheng Wang
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  7. Dapeng Tan
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Contributions

Dapeng Tan and Yuehua Wan conceived and designed the research; Zichao Yin and Lin Li analyzed the data; Hui Fang, Tong Wang and Zeng Wang contributed analysis tools and provided research platform. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Yuehua Wan or Dapeng Tan.

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Yin, Z., Wan, Y., Fang, H. et al. Bibliometric analysis on Brain-computer interfaces in a 30-year period. Appl Intell 53, 16205–16225 (2023). https://doi.org/10.1007/s10489-022-04226-4

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