Non-invasive Brain-Computer Interfaces: State of the Art and Trends

Bradley J. Edelman, Shuailei Zhang, Gerwin Schalk, Peter Brunner, Gernot Muller-Putz, Cuntai Guan, Bin He

Research output: Contribution to journalArticlepeer-review

Abstract

Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to widely influence research, clinical and recreational use. Non-invasive BCI approaches are particularly common as they can impact a large number of participants safely and at a relatively low cost. Where traditional non-invasive BCIs were used for simple computer cursor tasks, it is now increasingly common for these systems to control robotic devices for complex tasks that may be useful in daily life. In this review, we provide an overview of the general BCI framework as well as the various methods that can be used to record neural activity, extract signals of interest, and decode brain states. In this context, we summarize the current state-of-the-art of non-invasive BCI research, focusing on trends in both the application of BCIs for controlling external devices and algorithm development to optimize their use. We also discuss various open-source BCI toolboxes and software, and describe their impact on the field at large.

Original languageEnglish
Pages (from-to)1-25
Number of pages25
JournalIEEE Reviews in Biomedical Engineering
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • BCI
  • Brain-computer interface
  • Decoding
  • deep learning
  • Electrodes
  • Electroencephalography
  • electroencephalography
  • manifold classification
  • motor imagery
  • motor-related cortical potentials
  • Motors
  • neural decoding
  • neurotechnology
  • Recording
  • robotic arm
  • Robots
  • Task analysis
  • transfer learning

ASJC Scopus subject areas

  • Biomedical Engineering

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