Short time Fourier transformation and deep neural networks for motor imagery brain computer interface recognition

2018 ◽  
Vol 30 (23) ◽  
pp. e4413 ◽  
Author(s):  
Zijian Wang ◽  
Lei Cao ◽  
Zuo Zhang ◽  
Xiaoliang Gong ◽  
Yaoru Sun ◽  
...  
Keyword(s):  
Neural Networks ◽  
Motor Imagery ◽  
Fourier Transformation ◽  
Deep Neural Networks ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Short Time ◽  
Short Time Fourier Transformation

scholarly journals Classification of Emotions through EEG Signals using SVM and DNN

2020 ◽  
Vol 8 (5) ◽  
pp. 206-209
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Emotional State ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Work Place ◽  
Support Vector ◽  
Eeg Signals ◽  
Brain Signals

Emotions are important for Humans both at work place and in their life. Emotions helps us to communicate with others, to take decisions, in understand others etc., Emotions recognition not only helps us to solve the mental illness but also are important in various application such as Brain Computer Interface , medical care and entertainment This paper mainly deals with how Emotions are Classified through EEG Signals using SVM (Support Vector machine) and DNN (Deep Neural Networks) . Applying the most appropriate algorithm to detect the emotional state of a person and play the corresponding song in the playlist. Brain signals can be collected using EEG (electroencephalography) devices

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
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