Behaviour state analysis through brain computer interface using wearable EEG devices: a review

2017 ◽  
Vol 13 (4) ◽  
pp. 377
Author(s):  
Sravanth Kumar Ramakuri ◽  
Sanchita Ghosh ◽  
Bharat Gupta
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Wearable Eeg ◽  
State Analysis

scholarly journals Design of Wearable EEG Devices Specialized for Passive Brain–Computer Interface Applications

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4572 ◽  
Author(s):  
Seonghun Park ◽  
Chang-Hee Han ◽  
Chang-Hwan Im
Keyword(s):  
Brain Computer Interface ◽  
Temporal Correlation ◽  
General Purpose ◽  
Computer Interface ◽  
Accurate Estimation ◽  
Emotional States ◽  
Wearable Eeg ◽  
Conventional Electrode ◽  
Electroencephalogram Eeg

Owing to the increased public interest in passive brain–computer interface (pBCI) applications, many wearable devices for capturing electroencephalogram (EEG) signals in daily life have recently been released on the market. However, there exists no well-established criterion to determine the electrode configuration for such devices. Herein, an overall procedure is proposed to determine the optimal electrode configurations of wearable EEG devices that yield the optimal performance for intended pBCI applications. We utilized two EEG datasets recorded in different experiments designed to modulate emotional or attentional states. Emotion-specialized EEG headsets were designed to maximize the accuracy of classification of different emotional states using the emotion-associated EEG dataset, and attention-specialized EEG headsets were designed to maximize the temporal correlation between the EEG index and the behavioral attention index. General purpose electrode configurations were designed to maximize the overall performance in both applications for different numbers of electrodes (2, 4, 6, and 8). The performance was then compared with that of existing wearable EEG devices. Simulations indicated that the proposed electrode configurations allowed for more accurate estimation of the users’ emotional and attentional states than the conventional electrode configurations, suggesting that wearable EEG devices should be designed according to the well-established EEG datasets associated with the target pBCI applications.

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 ◽  
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