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 :
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