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Browsing by Subject "BCI"

Browsing by Subject "BCI"

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  • EEG-BASED PREDICTION OF SUCCESSFUL MEMORY FORMATION DURING VOCABULARY LEARNING 
    Kang, Taeho; Chen, Yiyu; Fazli, Siamac; Wallraven, Christian (Institute of Electrical and Electronics Engineers, 2020-09-10)
    Previous Electroencephalography (EEG) and neuroimaging studies have found differences between brain signals for subsequently remembered and forgotten items during learning of items - it has even been shown that single trial ...
  • EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy 
    Lee, Min-Ho; Kwon, O-Yeon; Kim, Yong-Jeong; Kim, Hong-Kyung; Lee, Young-Eun; Williamson, John; Fazli, Siamac; Lee, Seong-Whan (Oxford University Press, 2019-05)
    Background Electroencephalography (EEG)-based brain-computer interface (BCI) systems are mainly divided into three major paradigms: motor imagery (MI), event-related potential (ERP), and steady-state visually evoked ...
  • EXPLAINABLE DEEP LEARNING FOR BRAIN-COMPUTER INTERFACES 
    Mun, Vladislav (Nazarbayev University School of Engineering and Digital Sciences, 2022-05)
    A Brain-Computer Interface (BCI) is a continuously evolving technological framework that has been steadily gaining popularity over the past few decades. By recording the brain activity and structure through various means ...
  • META-CLASSIFICATION OF BRAIN SIGNALS IN P300 SPELLER 
    Mussabayeva, Ayana (Nazarbayev University School of Engineering and Digital Sciences, 2021-05)
    P300 Speller is a brain-computer interface (BCI) spelling system, which is used to enable a human to communicate with the outer world by processing electroencephalography (EEG) sig- nals. Such speller systems are usually ...
  • NON-ODDBALL ERP PARADIGMS WITH JOINT TEMPORAL-FREQUENCY LEARNING IN CONVOLUTIONAL NEURAL NETWORK 
    Saparbayeva, Madina (Nazarbayev University School of Engineering and Digital Sciences, 2022-04)
    Brain-Computer Interface (BCI) helps people who have a severe disease to interact with external devices. Event-Related Potential (ERP) based BCI systems send stimuli, then detect brain signals responding to stimuli. ...
  • PARADIGM-INDEPENDENT CLASSIFICATION ON MULTIDIMENSIONAL NEUROIMAGING DATASET USING CONVOLUTIONAL NEURAL NETWORKS 
    Alimanov, Kanat (Nazarbayev University School of Engineering and Digital Sciences, 2021-05)
    Brain-Computer Interfaces (BCI) are gaining popularity with each day. A lot of research was carried out to improve both accuracy and usability of individual BCI paradigms, most popular in current literature being Motor ...
  • Robust detection of event-related potentials in a user-voluntary short-term imagery task 
    Lee, Min-Ho; Williamson, John; Kee, Young-Jin; Fazli, Siamac; Lee, Seong-Whan (Public Library of Science, 2019-12)
    Event-related potentials (ERPs) represent neuronal activity in the brain elicited by external visual or auditory stimulation and are widely used in brain-computer interface (BCI) systems. The ERP responses are elicited a ...