A hybrid brain computer interface system based on the neurophysiological protocol and brain-actuated switch for wheelchair control

Background: Brain Computer Interfaces (BCIs) are developed to translate brain waves into machine instructions for external devices control. Recently, hybrid BCI systems are proposed for the multi-degree control of a real wheelchair to improve the systematical efficiency of traditional BCIs. However, it is difficult for existing hybrid BCIs to implement the multi-dimensional control in one command cycle. New method: This paper proposes a novel hybrid BCI system that combines motor imagery (MI)-based bio-signals and steady-state visual evoked potentials (SSVEPs) to control the speed and direction of a real wheelchair synchronously. Furthermore, a hybrid modalities-based switch is firstly designed to turn on/off the control system of the wheelchair. Results: Two experiments were performed to assess the proposed BCI system. One was implemented for training and the other one conducted a wheelchair control task in the real environment. All subjects completed these tasks successfully and no collisions occurred in the real wheelchair control experiment. Comparison with existing method(s): The protocol of our BCI gave much more control commands than those of previous MI and SSVEP-based BCIs. Comparing with other BCI wheelchair systems, the superiority reflected by the index of path length optimality ratio validated the high efficiency of our control strategy. Conclusions: The results validated the efficiency of our hybrid BCI system to control the direction and speed of a real wheelchair as well as the reliability of hybrid signals-based switch control. (C) 2014 Elsevier B.V. All rights reserved.