Combining ERD and ERS features to create a system-paced BCI

•Brief motor-imagery (MI) and post-MI features are exploited to design a brain computer interface (BCI).•Data from 3 electrodes are used to discriminate between 2 intentional control tasks and a no-control state.•The patterns used by BCI are demonstrated to be robust over time and are compatible with discrete feedback.•The results are validated by an online study performed in our laboratory with 6 subjects.

An important factor in the usability of a brain–computer interface (BCI) is the setup and calibration time required for the interface to perform accurately. Recently, brain-switches based on the beta rebound following motor imagery of a single limb effector have been investigated as basic BCIs due to their good performance with limited electrodes, and brief training session requirements. Here, a BCI is proposed which expands the methodology of brain-switches to design an interface composed of multiple brain-controlled buttons. The algorithm is designed as a system paced interface which can recognise 2 intentional-control tasks and a no-control state based on the activity during and following motor imagery in only 3 electroencephalogram channels. An online experiment was performed over 6 subjects to validate the algorithm, and the results show that a working BCI can be trained from a single calibration session and that the post motor imagery features are both informative and robust over multiple sessions.