Wheelchair navigation with an audio-cued, two-class motor imagery-based brain-computer interface system

Author

Varona-Moya, Sergio ; Velasco-Alvarez, Francisco ; Sancha-Ros, Salvador ; Fernandez-Rodriguez, Alvaro ; Blanca, Maria J. ; Ron-Angevin, Ricardo

Author_Institution

Dept. de Tecnol. Electron., Univ. de Malaga, Malaga, Spain

fYear

2015

fDate

22-24 April 2015

Firstpage

174

Lastpage

177

Abstract

Driving a real wheelchair by means of a brain-computer interface (BCI) system must be a reliable option for locked-in patients. Such navigation should also be autonomous, i.e., not depending on a ground chart. In this work we test the feasibility of driving a customized robotic wheelchair with a BCI system that our group has used in previous studies with virtual and real mobile robots. The results obtained from a sample of three healthy naïve participants suggest that it is an effective option, which could ultimately provide locked-in patients with greater autonomy and quality of life.

Keywords

brain-computer interfaces; electroencephalography; medical robotics; medical signal processing; mobile robots; neurophysiology; wheelchairs; BCI system; audio-cue; customized robotic wheelchair; healthy naive participants; locked-in patients; mobile robots; motor imagery-based brain-computer interface system; virtual robots; wheelchair navigation; Accuracy; Electroencephalography; Mobile robots; Navigation; Training; Wheelchairs;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on

Conference_Location

Montpellier

Type

conf

DOI

10.1109/NER.2015.7146588

Filename

7146588