scholarly journals Ergonomic Issues in Brain-Computer Interface Technologies: Current Status, Challenges, and Future Direction

2020 ◽  
Vol 2020 ◽  
pp. 1-2 ◽  
Author(s):  
Hyun Jae Baek ◽  
Hyun Seok Kim ◽  
Minkyu Ahn ◽  
Hohyun Cho ◽  
Sangtae Ahn
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Current Status ◽  
Future Direction

scholarly journals Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

2020 ◽  
Vol 14 ◽  
Author(s):  
Mamunur Rashid ◽  
Norizam Sulaiman ◽  
Anwar P. P. Abdul Majeed ◽  
Rabiu Muazu Musa ◽  
Ahmad Fakhri Ab. Nasir ◽  
...  
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Current Status ◽  
Comprehensive Review

Optimizing the P300-based brain–computer interface: current status, limitations and future directions

2011 ◽  
Vol 8 (2) ◽  
pp. 025003 ◽  
Author(s):  
J N Mak ◽  
Y Arbel ◽  
J W Minett ◽  
L M McCane ◽  
B Yuksel ◽  
...  
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Current Status ◽  
Future Directions

scholarly journals Progress in the Field of Micro-Electrocorticography

Micromachines ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 62 ◽  
Author(s):  
Mehdi Shokoueinejad ◽  
Dong-Wook Park ◽  
Yei Jung ◽  
Sarah Brodnick ◽  
Joseph Novello ◽  
...  
Keyword(s):  
Indium Tin Oxide ◽  
Electrode Materials ◽  
Brain Computer Interface ◽  
Electrode Array ◽  
Clinical Pathology ◽  
Computer Interface ◽  
Current Status ◽  
Signal Acquisition ◽  
Electrode Arrays ◽  
Advantages And Disadvantages

Since the 1940s electrocorticography (ECoG) devices and, more recently, in the last decade, micro-electrocorticography (µECoG) cortical electrode arrays were used for a wide set of experimental and clinical applications, such as epilepsy localization and brain–computer interface (BCI) technologies. Miniaturized implantable µECoG devices have the advantage of providing greater-density neural signal acquisition and stimulation capabilities in a minimally invasive fashion. An increased spatial resolution of the µECoG array will be useful for greater specificity diagnosis and treatment of neuronal diseases and the advancement of basic neuroscience and BCI research. In this review, recent achievements of ECoG and µECoG are discussed. The electrode configurations and varying material choices used to design µECoG arrays are discussed, including advantages and disadvantages of µECoG technology compared to electroencephalography (EEG), ECoG, and intracortical electrode arrays. Electrode materials that are the primary focus include platinum, iridium oxide, poly(3,4-ethylenedioxythiophene) (PEDOT), indium tin oxide (ITO), and graphene. We discuss the biological immune response to µECoG devices compared to other electrode array types, the role of µECoG in clinical pathology, and brain–computer interface technology. The information presented in this review will be helpful to understand the current status, organize available knowledge, and guide future clinical and research applications of µECoG technologies.

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.

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