Asynchronous Brain-Computer Interfacing Based on Mixed-Coded Visual Stimuli.

OBJECTIVE

One of the challenges in the area of brain-computer interfacing (BCI) is to develop an asynchronous BCI or a self-paced BCI that detects whether a user intends to pass messages. This paper proposes a novel asynchronous BCI that uses mixed frequency and phase-coded visual stimuli, which can provide high-speed and accurate command entries.

METHODS

The mixed-coded visual stimuli were presented as flickers with a following blank interval to synchronize the recorder of electroencephalogram (EEG) with the stimuli, which was aimed to detect the phase in an asynchronous situation. For decoding from the measured EEG, multiset canonical correlation analysis (MCCA) was efficiently exploited for recognizing the intentional state and the intending command. The proposed asynchronous BCI was tested on 11 healthy subjects.

RESULTS

The proposed decoder was capable of discriminating between the intentional control/noncontrol state and determining the command faster and more accurately than the contrast methods, achieving area under the curve of 0.9191 $\pm$ 0.1206 and command recognition accuracy of 91.08 $\pm$ 13.97 $%$ with data lengths of 3.0 s.

CONCLUSION

The BCI based on mixed-coded visual stimuli was able to be implemented in an asynchronous manner, and the MCCA-based decoder outperformed the conventional ones in terms of discriminability of intentional states and command recognition accuracy.

SIGNIFICANCE

The present study showed that an asynchronous BCI can be implemented with mixed-coded visual stimuli for the first time, which enables a large increase in the number of choices/commands.