An application of online ANFIS classifier for wheelchair based brain computer interface

2015 ◽  
Author(s):  
Mardi Turnip ◽  
Abdi Dharma ◽  
Hendra H. S. Pasaribu ◽  
Mawaddah Harahap ◽  
M. Faizal Amri ◽  
...  
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Anfis Classifier

Simultaneous Classification of Multiple Motor Imagery and P300 for Increase in Output Information of Brain-computer Interface

2013 ◽  
Vol 133 (3) ◽  
pp. 635-641
Author(s):  
Genzo Naito ◽  
Lui Yoshida ◽  
Takashi Numata ◽  
Yutaro Ogawa ◽  
Kiyoshi Kotani ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Output Information

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

Brain Control: Human-computer Integration Control Based on Brain-computer Interface

2014 ◽  
Vol 39 (3) ◽  
pp. 208-221 ◽  
Author(s):  
Xing-Yu WANG ◽  
Jing JIN ◽  
Yu ZHANG ◽  
Bei WANG
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Computer Integration
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