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 …
An introductory tutorial on brain–computer interfaces and their applications
The prospect and potentiality of interfacing minds with machines has long captured human
imagination. Recent advances in biomedical engineering, computer science, and …
imagination. Recent advances in biomedical engineering, computer science, and …
A novel training-free recognition method for SSVEP-based BCIs using dynamic window strategy
Objective. Filter bank canonical correlation analysis (FBCCA) is a widely-used classification
approach implemented in steady-state visual evoked potential (SSVEP)–based brain …
approach implemented in steady-state visual evoked potential (SSVEP)–based brain …
Correlated component analysis for enhancing the performance of SSVEP-based brain-computer interface
A new method for steady-state visual evoked potentials (SSVEPs) frequency recognition is
proposed to enhance the performance of SSVEP-based brain-computer interface (BCI) …
proposed to enhance the performance of SSVEP-based brain-computer interface (BCI) …
Two-stage frequency recognition method based on correlated component analysis for SSVEP-based BCI
A canonical correlation analysis (CCA) is a state-of-the-art method for frequency recognition
in steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) …
in steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) …
Novel Signal-to-Signal translation method based on StarGAN to generate artificial EEG for SSVEP-based brain-computer interfaces
Generative adversarial networks (GANs) have shown promising performance in image-to-
image translation. Inspired by StarGAN v2, which was introduced to address the …
image translation. Inspired by StarGAN v2, which was introduced to address the …
A training data-driven canonical correlation analysis algorithm for designing spatial filters to enhance performance of SSVEP-based BCIs
Canonical correlation analysis (CCA) is an effective spatial filtering algorithm widely used in
steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). In …
steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). In …
Multiband tangent space mapping and feature selection for classification of EEG during motor imagery
Objective. When designing multiclass motor imagery-based brain–computer interface (MI-
BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of …
BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of …
Multiband entropy-based feature-extraction method for automatic identification of epileptic focus based on high-frequency components in interictal iEEG
MS Akter, MR Islam, Y Iimura, H Sugano, K Fukumori… - Scientific reports, 2020 - nature.com
Presurgical investigations for categorizing focal patterns are crucial, leading to localization
and surgical removal of the epileptic focus. This paper presents a machine learning …
and surgical removal of the epileptic focus. This paper presents a machine learning …
Incorporating neighboring stimuli data for enhanced SSVEP-based BCIs
Various spatial filters have been proposed to enhance the target identification performance
of steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) …
of steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) …