Current trends in Graz brain-computer interface (BCI) research

2000 ◽  
Vol 8 (2) ◽  
pp. 216-219 ◽  
Author(s):  
G. Pfurtscheller ◽  
C. Neuper ◽  
C. Guger ◽  
W. Harkam ◽  
H. Ramoser ◽  
...  
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Current Trends

scholarly journals Motor Imagery EEG Classification based on Machine Learning Algorithm

2020 ◽  
Vol 8 (6) ◽  
pp. 5235-5246
Keyword(s):  
Nervous System ◽  
Motor Imagery ◽  
Learning Algorithm ◽  
Brain Computer Interface ◽  
Medical Science ◽  
System Optimization ◽  
Neural System ◽  
Optimization Techniques ◽  
Computer Interface ◽  
Current Trends

The advancement of computer technology facilitates in the field of medical science for the analysis of complex Diseases related to the neurology. These technologies named as BCI (brain computer interface). The BCI is open area of research for physically challenge people such as paralyzed and amputees. The current technology of computer interface interest in EEG (electroencephalographic) for the analysis of signals for the predication of nervous system. The current trends of brain computer interface focus on process signal of EEG for the sense of human body behaviors and movement of nervous system, motor imagery and various senses. The gathered signal by the EEG is very noisy and predication and recognition of the motor imagery is typical. The minimization of noise upgrades the predication procedure and examination of signal behaviors. For the analysis of behaviors system utilized soft computing processing approach, for example, neural system, optimization techniques. The component extraction and feature selection are also major issue in motor imagery analysis for critical and complex disorder of human brain system.

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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