EEG-based hybrid BCIs and their applications

Abstract

In this paper, we presented two hybrid brain computer interfaces (BCIs), one combing motor imagery (MI) and P300 and another combing P300 and steady state visual evoked potential (SSVEP), and their applications. An important issue in BCI research is multidimensional control. Potential applications include BCI controlled computer mouse, document and email processing, web browser, wheelchair and neuroprosthesis. The challenge for EEG-based multidimensional control is to obtain multiple independent control signals from the noisy EEG data. For this purpose, hybrid BCIs may yield better performance than BCIs those use only one type of brain pattern. In this project, we first developed a hybrid system for 2-D cursor control. In our system, two independent signals based on MI and P300 were produced from EEG for the vertical and horizontal movement control of the cursor respectively, and the cursor can be moved from an arbitrary initial position to a randomly given target position. Furthermore, a hybrid feature was extracted for selecting the target-of-interest and rejecting the target-of-no-interest, as fast and accurate as possible. In this way, a BCI mouse was implemented. Then an internet browser and a mail client were developed based on the BCI mouse. Moreover, we extended this hybrid BCI system to control a virtual car/wheelchair. On the other hand, we also developed a P300 and SSVEP-based hybrid BCI not only to improve the classification performance, but also to validate the possibility of clinical applications, e.g., detection of residual cognitive function and covert awareness in patients with disorders of consciousness.