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A high-performance SSVEP-based BCI using imperceptible flickers.

Gege Ming1,2, Weihua Pei1,2, Xiaorong Gao3

  • 1State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, People's Republic of China.

Journal of Neural Engineering
|January 20, 2023
PubMed
Summary
This summary is machine-generated.

This study developed an individualized brain-computer interface (BCI) using steady-state visual evoked potentials (SSVEPs) by modulating imperceptible 60 Hz flickers. The novel approach enhances BCI performance and user experience by personalizing visual stimulation based on individual brain activity.

Keywords:
brain-computer interfaceselectroencephalographyimperceptible flickerssteady-state visual evoked potentialstask-related component analysis

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Existing steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) face challenges in balancing user experience and system performance.
  • Individual variability in cortex geometry affects the efficacy of current SSVEP-BCI systems.

Purpose of the Study:

  • To propose and evaluate an individualized space and phase modulation method for coding imperceptible 60 Hz flickers.
  • To enhance the performance and user-friendliness of SSVEP-based BCIs by personalizing visual stimulation.

Main Methods:

  • An annulus global-stimulation was divided into local-stimulations, with SSVEPs superimposed to simulate global-stimulation SSVEPs using space and phase coding.
  • A four-class phase-coded BCI diagram was used to evaluate simulated classification performance.
  • An online BCI system with 60 Hz SSVEPs was implemented across five modulation groups, including individualized optimal, medium, worst, standard-modulation, and non-modulation groups, with user experience assessed via questionnaires.

Main Results:

  • The individualized space and phase modulation effectively modulated SSVEP intensity without compromising user experience.
  • The online BCI system achieved high information transfer rates, with the individualized optimal-modulation group reaching 52.8 ± 1.9 bits min⁻¹.
  • Individualized worst-modulation and non-modulation groups achieved rates of 16.8 ± 2.4 bits min⁻¹ and 42.4 ± 3.0 bits min⁻¹, respectively.

Conclusions:

  • Exploiting structural and functional characteristics of the human visual cortex enhances SSVEP response intensity at 60 Hz.
  • The proposed method results in a high-performance BCI system with good user experience.
  • This study holds significant theoretical and application value for advancing visual BCI technology.