Brain–computer interface speller based on steady-state visual evoked potential: A review focusing on the stimulus paradigm and performance
The steady-state visual evoked potential (SSVEP), measured by the electroencephalograph
(EEG), has high rates of information transfer and signal-to-noise ratio, and has been used to …
(EEG), has high rates of information transfer and signal-to-noise ratio, and has been used to …
To train or not to train? A survey on training of feature extraction methods for SSVEP-based BCIs
Objective. Despite the vast research aimed at improving the performance of steady-state
visually evoked potential (SSVEP)-based brain–computer interfaces (BCIs), several …
visually evoked potential (SSVEP)-based brain–computer interfaces (BCIs), several …
Correlation-based channel selection and regularized feature optimization for MI-based BCI
Multi-channel EEG data are usually necessary for spatial pattern identification in motor
imagery (MI)-based brain computer interfaces (BCIs). To some extent, signals from some …
imagery (MI)-based brain computer interfaces (BCIs). To some extent, signals from some …
Improving the performance of individually calibrated SSVEP-BCI by task-discriminant component analysis
A brain-computer interface (BCI) provides a direct communication channel between a brain
and an external device. Steady-state visual evoked potential based BCI (SSVEP-BCI) has …
and an external device. Steady-state visual evoked potential based BCI (SSVEP-BCI) has …
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 …
A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
The robust analysis of neural signals is a challenging problem. Here, we contribute a
convolutional neural network (CNN) for the robust classification of a steady-state visual …
convolutional neural network (CNN) for the robust classification of a steady-state visual …
A comparison study of canonical correlation analysis based methods for detecting steady-state visual evoked potentials
Canonical correlation analysis (CCA) has been widely used in the detection of the steady-
state visual evoked potentials (SSVEPs) in brain-computer interfaces (BCIs). The standard …
state visual evoked potentials (SSVEPs) in brain-computer interfaces (BCIs). The standard …
Optimizing spatial patterns with sparse filter bands for motor-imagery based brain–computer interface
Background Common spatial pattern (CSP) has been most popularly applied to motor-
imagery (MI) feature extraction for classification in brain–computer interface (BCI) …
imagery (MI) feature extraction for classification in brain–computer interface (BCI) …
BETA: A large benchmark database toward SSVEP-BCI application
The brain-computer interface (BCI) provides an alternative means to communicate and it has
sparked growing interest in the past two decades. Specifically, for Steady-State Visual …
sparked growing interest in the past two decades. Specifically, for Steady-State Visual …
Spatial filtering in SSVEP-based BCIs: Unified framework and new improvements
Objective: In the steady-state visual evoked potential (SSVEP)-based brain computer
interfaces (BCIs), spatial filtering, which combines the multi-channel …
interfaces (BCIs), spatial filtering, which combines the multi-channel …