Hybrid P300 and mu-beta brain computer interface to operate a brain controlled wheelchair

Authors:
B. Rebsamen;E. Burdet;Q. Zeng;H. Zhang;M. Ang;C. L. Teo;C. Guan;C. Laugier
Affiliations:
National University of Singapore;Imperial College London, UK;National University of Singapore;Institute for Infocomm Research, A*STAR, Singapore;National University of Singapore;National University of Singapore;Institute for Infocomm Research, A*STAR, Singapore;INRIA Rhône-Alpes, France
Venue:
Proceedings of the 2nd International Convention on Rehabilitation Engineering & Assistive Technology
Year:
2008

Citing 3
Cited 1

Controlling a Wheelchair Indoors Using Thought

IEEE Intelligent Systems
Electroencephalogram-Based Control of an Electric Wheelchair

IEEE Transactions on Robotics
A local neural classifier for the recognition of EEG patterns associated to mental tasks

IEEE Transactions on Neural Networks

A review of hybrid brain-computer interface systems

Advances in Human-Computer Interaction - Special issue on Using Brain Waves to Control Computers and Machines

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a control strategy to drive a wheelchair in a building environment by thought. The user selects the destination in a list of predefined locations of interest using a slow but safe P300 EEG interface. The robotic wheelchair navigates autonomously toward destination following virtual guiding paths. Along the way the user has the possibility to stop the movement using a fast μβ-rhythm BCI. Experiments demonstrate how healthy subjects can navigate safely in an home-like environment using this novel hybrid BCI.