DocumentCode
1674317
Title
Non-invasive brain signal interface for a wheelchair navigation
Author
Shin, Bong-Gun ; Kim, Taesoo ; Jo, Sungho
Author_Institution
Dept. of Comput. Sci., KAIST, Daejeon, South Korea
fYear
2010
Firstpage
2257
Lastpage
2260
Abstract
This work presents that, only using non-invasively captured brain signals, a person can navigate an electric wheelchair with no serious training for a long term. Only two electrodes are set on the scalp non-invasively to detect a P300 EEG signal and a reference signal. A simple signal processing interprets the measured signals to decide a movement direction of the wheelchair. The whole devices are loaded on the wheelchair. No external system is required. The experimental results demonstrate the feasibility of the simple BCI processing to achieve reasonable performance.
Keywords
brain-computer interfaces; electroencephalography; medical signal processing; signal detection; wheelchairs; BCI processing; P300 EEG signal detection; electric wheelchair; noninvasive brain signal interface; reference signal detection; signal measurement; signal processing; wheelchair navigation; Computers; DC motors; Electrodes; Electroencephalography; Navigation; Training; Wheelchairs; Brain-machine interface; EEG; P300; wheelchair control;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Automation and Systems (ICCAS), 2010 International Conference on
Conference_Location
Gyeonggi-do
Print_ISBN
978-1-4244-7453-0
Electronic_ISBN
978-89-93215-02-1
Type
conf
Filename
5669830
Link To Document