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Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications.

Zina Li1, Shuqing Zhang1, Jiahui Pan1

  • 1South China Normal University, Guangzhou 510631, China.

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Hybrid brain-computer interfaces (hBCI) overcome limitations in conventional brain-computer interface (BCI) systems. hBCI technology enhances detection performance and enables advanced, multifunctional control.

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Area of Science:

  • Neuroscience and Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Conventional brain-computer interface (BCI) systems struggle with low detection accuracy and limited control capabilities.
  • These limitations hinder the practical application and effectiveness of BCI technology in various fields.

Purpose of the Study:

  • To review the research progress and advancements in hybrid brain-computer interface (hBCI) systems.
  • To explore novel hBCI approaches for overcoming the challenges faced by traditional BCI.
  • To evaluate the performance and potential of hBCI in improving BCI applications.

Main Methods:

  • Review of three types of hBCI: those based on multiple brain models, multisensory integration, and multimodal signal utilization.
  • Analysis of general principles, experimental paradigms, and results of the latest hBCI systems.
  • Examination of the advantages and application scope of different hBCI strategies.

Main Results:

  • Hybrid brain-computer interface (hBCI) technology significantly improves detection performance compared to single-mode BCIs.
  • hBCI enables multidegree and multifunctional control, offering enhanced command capabilities.
  • The reviewed hBCI approaches demonstrate superior performance and broader applicability.

Conclusions:

  • Hybrid brain-computer interfaces represent a significant advancement over conventional BCI systems.
  • hBCI technology effectively addresses key challenges in detection and control, paving the way for more sophisticated brain-computer interaction.
  • The findings support the adoption of hBCI for developing next-generation assistive and control technologies.