Robust similarity measurement based on a novel time filter for SSVEPs detection
The steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has
received extensive attention in research for the less training time, excellent recognition …
received extensive attention in research for the less training time, excellent recognition …
EEG channel selection techniques in motor imagery applications: a review and new perspectives
Communication, neuro-prosthetics, and environmental control are just a few applications for
disabled persons who use robots and manipulators that use brain-computer interface (BCI) …
disabled persons who use robots and manipulators that use brain-computer interface (BCI) …
Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features
Schizophrenia is a mental disorder that causes adverse effects on the mental capacity of a
person, emotional inclinations, and quality of personal and social life. The official statistics …
person, emotional inclinations, and quality of personal and social life. The official statistics …
Developing a motor imagery-based real-time asynchronous hybrid BCI controller for a lower-limb exoskeleton
This study aimed to develop an intuitive gait-related motor imagery (MI)-based hybrid brain-
computer interface (BCI) controller for a lower-limb exoskeleton and investigate the …
computer interface (BCI) controller for a lower-limb exoskeleton and investigate the …
Feature extraction method based on filter banks and Riemannian tangent space in motor-imagery BCI
Optimal feature extraction for multi-category motor imagery brain-computer interfaces (MI-
BCIs) is a research hotspot. The common spatial pattern (CSP) algorithm is one of the most …
BCIs) is a research hotspot. The common spatial pattern (CSP) algorithm is one of the most …
SincNet-based hybrid neural network for motor imagery EEG decoding
It is difficult to identify optimal cut-off frequencies for filters used with the common spatial
pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most …
pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most …
Motor imagery EEG signal classification using image processing technique over GoogLeNet deep learning algorithm for controlling the robot manipulator
Controlling of a robotic arm using a brain-computer interface (BCI) is one of the most
impressive applications. In this study, a novel method for the classification of motor imaging …
impressive applications. In this study, a novel method for the classification of motor imaging …
Multi-scale neural network for EEG representation learning in BCI
Recent advances in deep learning have had a methodological and practical impact on brain-
computer interface (BCI) research. Among the various deep network architectures …
computer interface (BCI) research. Among the various deep network architectures …
The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Brain-computer interface (BCI) is a viable alternative communication strategy for patients of
neurological disorders as it facilitates the translation of human intent into device commands …
neurological disorders as it facilitates the translation of human intent into device commands …
Improved sparse representation based robust hybrid feature extraction models with transfer and deep learning for EEG classification
SK Prabhakar, SW Lee - Expert Systems with Applications, 2022 - Elsevier
Numerous studies in the field of cognitive research is dependent on
Electroencephalography (EEG) as it apprehends the neural correspondences of various …
Electroencephalography (EEG) as it apprehends the neural correspondences of various …