Title :
EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface
Author :
Gandhi, V. ; Prasad, Girijesh ; Coyle, D. ; Behera, Laxmidhar ; McGinnity, Thomas Martin
Author_Institution :
Sch. of Sci. & Technol., Middlesex Univ., London, UK
Abstract :
A major challenge in two-class brain-computer interface (BCI) systems is the low bandwidth of the communication channel, especially while communicating and controlling assistive devices, such as a smart wheelchair or a telepresence mobile robot, which requires multiple motion command options in the form of forward, left, right, backward, and start/stop. To address this, an adaptive user-centric graphical user interface referred to as the intelligent adaptive user interface (iAUI) based on an adaptive shared control mechanism is proposed. The iAUI offers multiple degrees-of-freedom control of a robotic device by providing a continuously updated prioritized list of all the options for selection to the BCI user, thereby improving the information transfer rate. Results have been verified with multiple participants controlling a simulated as well as physical pioneer robot.
Keywords :
adaptive control; adaptive systems; brain-computer interfaces; control engineering computing; electroencephalography; graphical user interfaces; mobile robots; service robots; telecommunication channels; BCI systems; EEG-based mobile robot control; adaptive brain-robot interface system; communicating assistive devices; communication channel; controlling assistive devices; graphical user interface; iAUI; information transfer rate; intelligent adaptive user interface; multiple degree-of-freedom control; physical pioneer robot; robotic device; Accuracy; Graphical user interfaces; Mobile robots; Robot sensing systems; Wheelchairs; Brain-computer interface (BCI); Brain??computer interface (BCI); graphical user interface; motor imagery; wheelchair/robot;
Journal_Title :
Systems, Man, and Cybernetics: Systems, IEEE Transactions on
DOI :
10.1109/TSMC.2014.2313317