fNIRS-Based Brain–Computer Interface Using Deep Neural Networks for Classifying the Mental State of Drivers

2018 ◽  
pp. 353-362 ◽  
Author(s):  
Gauvain Huve ◽  
Kazuhiko Takahashi ◽  
Masafumi Hashimoto
Keyword(s):  
Neural Networks ◽  
Mental State ◽  
Deep Neural Networks ◽  
Brain Computer Interface ◽  
Computer Interface

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

Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction

2021 ◽  
pp. 108359
Author(s):  
Christian Flores Vega ◽  
Jonathan Quevedo ◽  
Elmer Escandón ◽  
Mehrin Kiani ◽  
Weiping Ding ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Smart Home ◽  
Brain Computer Interface ◽  
Computer Interface
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