A Hybrid BCI System Combining P300 and SSVEP and Its Application to Wheelchair Control

Abstract

In this paper, a hybrid brain-computer interface (BCI) system combining P300 and steady-state visual evoked potential (SSVEP) is proposed to improve the performance of asynchronous control. The four groups of flickering buttons were set in the graphical user interface. Each group contained one large button in the center and eight small buttons around it, all of which flashed at a fixed frequency (e.g., 7.5 Hz) to evoke SSVEP. At the same time, the four large buttons of the four groups were intensified through shape and color changes in a random order to produce P300 potential. During the control state, the user focused on a desired group of buttons (target buttons) to evoke P300 potential and SSVEP, simultaneously. Discrimination between the control and idle states was based on the detection of both P300 and SSVEP on the same group of buttons. As an application, this method was used to produce a "go/stop" command in real-time wheelchair control. Several experiments were conducted, and data analysis results showed that combining P300 potential and SSVEP significantly improved the performance of the BCI system in terms of detection accuracy and response time.

Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface

“…Naseer et al (2014) have shown binary decision decoding for rehabilitation, whereas in this research the four control commands can be associated to four different decisions. Moreover, the previous hybrid EEG based researches for rehabilitation have shown the use of P300 and steady state visual evoked potentials (Li et al, 2013; Xu et al, 2013) to generate four control commands based on reactive tasks. As motor imagery and motor execution activate the same brain area (Beisteiner et al, 1995; Porro et al, 1996), the same goal can be achived by this research using active tasks.…”

SOPHIA: Soft Orthotic Physiotherapy Hand Interactive Aid

“…BMIs have been proposed for motor neurorehabilitation, motor replacement and assistive technologies (de Almeida Ribeiro et al, 2013), and wheelchair control (Li et al, 2013). Previous work by RamosMurguialday et al (2013) with chronic (post 2 weeks) stroke patients showed that patients using-BMIs recovered a wider range of movements than the placebo group.…”

Hybrid brain–computer interface for biomedical cyber-physical system application using wireless embedded EEG systems

“…As a result, hybrid EEG-based BCI has been developed using the combination of different mental strategies [41]. Currently, most of the hybrid EEG-based BCIs use the combination of motor imagery with SSVEP [40] and P300 with SSVEP [42–45]. …”