Past, present, and future of EEG-based BCI applications
K Värbu, N Muhammad, Y Muhammad - Sensors, 2022 - mdpi.com
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …
provides a pathway between the brain and external devices by interpreting EEG. EEG …
Single-trial analysis and classification of ERP components—a tutorial
Analyzing brain states that correspond to event related potentials (ERPs) on a single trial
basis is a hard problem due to the high trial-to-trial variability and the unfavorable ratio …
basis is a hard problem due to the high trial-to-trial variability and the unfavorable ratio …
High-speed spelling with a noninvasive brain–computer interface
The past 20 years have witnessed unprecedented progress in brain–computer interfaces
(BCIs). However, low communication rates remain key obstacles to BCI-based …
(BCIs). However, low communication rates remain key obstacles to BCI-based …
Multisource transfer learning for cross-subject EEG emotion recognition
Electroencephalogram (EEG) has been widely used in emotion recognition due to its high
temporal resolution and reliability. Since the individual differences of EEG are large, the …
temporal resolution and reliability. Since the individual differences of EEG are large, the …
Investigating the use of pretrained convolutional neural network on cross-subject and cross-dataset EEG emotion recognition
Y Cimtay, E Ekmekcioglu - Sensors, 2020 - mdpi.com
The electroencephalogram (EEG) has great attraction in emotion recognition studies due to
its resistance to deceptive actions of humans. This is one of the most significant advantages …
its resistance to deceptive actions of humans. This is one of the most significant advantages …
Transfer learning in brain-computer interfaces
The performance of brain-computer interfaces (BCIs) improves with the amount of available
training data; the statistical distribution of this data, however, varies across subjects as well …
training data; the statistical distribution of this data, however, varies across subjects as well …
A benchmark dataset for SSVEP-based brain–computer interfaces
This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset
acquired with a 40-target brain-computer interface (BCI) speller. The dataset consists of 64 …
acquired with a 40-target brain-computer interface (BCI) speller. The dataset consists of 64 …
Domain adaptation techniques for EEG-based emotion recognition: a comparative study on two public datasets
Affective brain-computer interface (aBCI) introduces personal affective factors to human-
computer interaction. The state-of-the-art aBCI tailors its classifier to each individual user to …
computer interaction. The state-of-the-art aBCI tailors its classifier to each individual user to …
Neurophysiological predictor of SMR-based BCI performance
Brain–computer interfaces (BCIs) allow a user to control a computer application by brain
activity as measured, eg, by electroencephalography (EEG). After about 30years of BCI …
activity as measured, eg, by electroencephalography (EEG). After about 30years of BCI …
Spatio-spectral feature representation for motor imagery classification using convolutional neural networks
Convolutional neural networks (CNNs) have recently been applied to electroencephalogram
(EEG)-based brain–computer interfaces (BCIs). EEG is a noninvasive neuroimaging …
(EEG)-based brain–computer interfaces (BCIs). EEG is a noninvasive neuroimaging …