Asynchronous Brain–Computer Interface Based on Steady-State Visual-Evoked Potential

Asynchronous brain–computer interface (BCI) systems are more practicable than synchronous ones in real-world applications. A key challenge in asynchronous BCI design is to discriminate intentional control (IC) and non-intentional control (NC) states. In this paper, we present a two-stage asynchronous protocol for a steady-state visual-evoked potential-based BCI. First, we estimate a threshold using canonical correlation analysis coefficients in synchronous mode; then, we combine it with a sliding window strategy to continuously detect the mental state of the user. If the current state is judged as an IC state, then the system will output command. Our results show that the average positive predictive value of the system is 77.06  % and that its average false-positive rate in the NC state and IC state are 2.37 and 12.05 %, respectively.