Recent Advances in the Design of a 3-State Self-Paced (Asynchronous) Brain Computer Interface

Unlike synchronous brain computer interfaces (BCI), self-paced (asynchronous) BCIs have the advantage of being operational at all times. A 3-state self-paced BCI is capable of detecting two different brain states (e.g. two movements) from the ongoing EEG, while a 2-state one can only detect one brain state. This study improves the performance of a 3-state self-paced BCI designed to detect right and left hand extension movements. Instead of using the values of features at each instant of time, the improved BCI uses all past features´ values to detect the presence of a movement at any specific time. After detecting the presence of a movement, the system uses spectral features to determine whether the detected movement is a right or a left hand extension. Using data from two able-bodied individuals, it is shown that the correct detection of a right or a left hand movement, on average, increases from 44.3% to 55.9%, for a fixed false positive rate of 1%. In differentiating between right and left hand movements the average performance increases from 64% to 68.5%. At the false positive rate of 0.5%, the average true positive rate increases from 20.2% to 27.6% and the differentiation rate between right and left hand extensions increase from 71% to is 72.5%.