JOURNAL ARTICLE

EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface

Vaibhav GandhiGirijesh PrasadDamien CoyleLaxmidhar BeheraT.M. McGinnity

Year: 2014 Journal:   IEEE Transactions on Systems Man and Cybernetics Systems Vol: 44 (9)Pages: 1278-1285   Publisher: Institute of Electrical and Electronics Engineers

Abstract

A major challenge in two-class brain–computer interface \n(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 \nmotion 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 \nmultiple 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:
Brain–computer interface Computer science Human–computer interaction Mobile robot Information transfer Robot Interface (matter) Wheelchair Robot control Artificial intelligence Electroencephalography Telecommunications

Metrics

106
Cited By
5.13
FWCI (Field Weighted Citation Impact)
11
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Gaze Tracking and Assistive Technology
Physical Sciences →  Computer Science →  Human-Computer Interaction
Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience

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