An Tactile ERP-Based Brain–Computer Interface for Communication

Abstract

A classical visual event relative potential (ERP) brain–computer interface (BCI) system relies on visual stimuli to choose commands. Users obtain most information about their surroundings visually as well. This large amount of information can aggravate visual burden and fatigue. In our study, we proposed a novel approach to evoke ERP with a tactile stimulus. To achieve this approach, we first designed a wireless stimulus module with vibrators to provide a tactile stimulus for the system. The vibrators were located on the subject’s arm to imitate the joint motion of a robotic arm. Then, the ERP feature and the parameters of classifiers were obtained through offline experimental data analysis. Based on the analysis, the suitable electrode channels, stimulus onset asynchrony (SOA), and filter upper limit were different for different subjects. According to those outcomes, a unique classifier was designed for each subject. Finally, 10 healthy BCI-naive subjects participated in online experiments to evaluate the performance of our tactile BCI system; they achieved an accuracy range from 78.67% to 100% with an average of 89.1% and an instantaneous transmission rate (ITR) range from 7.77 to 28.70 bits/min with an average of 14.77 bits/min. The accuracy of different subjects and SOAs remained relatively stable, the ITR fluctuated mainly due to the different SOAs, and we achieved balance between ITR and accuracy.