A High-Speed Visual BCI Based on Hybrid Frequency–Phase–Space Encoding and High-Density EEG Decoding

TL;DR

This paper introduces a high-speed visual brain-computer interface using a new encoding method and high-density EEG to significantly improve communication speed.

Contribution

The novel hybrid frequency–phase–space encoding method with high-density EEG boosts information transfer rates in visual BCIs.

Findings

Using 66/256, 32/128, and 21/64 electrode configurations increased theoretical ITR by up to 195.56% in a 200-target BCI paradigm.

The online system achieved an average ITR of 472.72 bits per minute, demonstrating practical high-speed performance.

Spatiotemporal encoding and electrode density jointly determine achievable ITRs in visual BCIs.

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 hybrid frequency–phase–space encoding method, integrated with high-density electroencephalogram (EEG) recordings, to develop high-speed BCI systems. EEG data were recorded using a 256-channel standard cap, and 4 electrode configurations comprising 66, 32, 21, and 9 parieto-occipital electrodes, extracted from 256-, 128-, and 64-channel caps (abbreviated as 66/256, 32/128, 21/64, and 9/64), were systematically compared. In the classical frequency–phase encoding the 40-target BCI paradigm, the 66/256, 32/128, and 21/64 electrode configurations brought theoretical ITR increases of 83.66%, 79.99%, and 55.50% over the traditional 9/64 setup. In the proposed frequency–phase–space encoding 200-target BCI paradigm, these increases climbed to 195.56%, 153.08%, and 103.07%, respectively. The online BCI system achieved an average actual ITR of (472.72 ± 15.06) bits per minute. Taken together, these findings clarify how the spatiotemporal encoding strategy and electrode density jointly determine achievable ITRs and provide quantitative design guidelines for future high-speed visual BCIs.

Figures