High-Density EEG Enables the Fastest Visual Brain-Computer Interfaces

TL;DR

This study introduces a high-density EEG-based visual BCI system with a novel encoding method, significantly increasing information transfer rates and enabling faster, more efficient brain-computer communication.

Contribution

It presents a frequency-phase-space fusion encoding technique combined with 256-channel EEG, achieving unprecedented ITRs in visual BCI paradigms.

Findings

The proposed method increases ITR by over 80% in 40-target BCI.

Achieved an average ITR of 472.7 bpm in online testing.

High-density EEG effectively captures spatiotemporal brain signals for BCI.

Abstract

Brain-computer interface (BCI) technology establishes a direct communication pathway between the brain and external devices. Current visual BCI systems suffer from insufficient information transfer rates (ITRs) for practical use. Spatial information, a critical component of visual perception, remains underexploited in existing systems because the limited spatial resolution of recording methods hinders the capture of the rich spatiotemporal dynamics of brain signals. This study proposed a frequency-phase-space fusion encoding method, integrated with 256-channel high-density electroencephalogram (EEG) recordings, to develop high-speed BCI systems. In the classical frequency-phase encoding 40-target BCI paradigm, the 256-66, 128-32, and 64-21 electrode configurations brought theoretical ITR increases of 83.66%, 79.99%, and 55.50% over the traditional 64-9 setup. In the proposed frequency-phase-space encoding 200-target BCI paradigm, these increases climbed to 195.56%, 153.08%, and 103.07%. The online BCI system achieved an average actual ITR of 472.7 bpm. This study demonstrates the essential role and immense potential of high-density EEG in decoding the spatiotemporal information of visual stimuli.