Feature learning framework based on EEG graph self-attention networks for motor imagery BCI systems

KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification

(2023) Daniel Guillermo García-Murillo et al.   Diagnostics

A lightweight and accurate double-branch neural network for four-class motor imagery classification

(2022) Weifeng Ma et al.   Biomedical Signal Processing and Control

EEG-inception: an accurate and robust end-to-end neural network for EEG-based motor imagery classification

(2021) Ce Zhang et al.   Journal of Neural Engineering

A novel multi-scale convolutional neural network for motor imagery classification

(2021) Mouad Riyad et al.   Biomedical Signal Processing and Control

Feature Selection Combining Filter and Wrapper Methods for Motor-Imagery Based Brain–Computer Interfaces

(2021) Hao Sun et al.   International Journal of Neural Systems

A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery Based Brain-Computer Interface

(2021) Jing Jin et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Learning EEG topographical representation for classification via convolutional neural network

(2020) Meiyan Xu et al.   PATTERN RECOGNITION

Novel channel selection method based on position priori weighted permutation entropy and binary gravity search algorithm

(2020) Hao Sun et al.   Cognitive Neurodynamics

Multiple Kernel Stein Spatial Patterns for the Multiclass Discrimination of Motor Imagery Tasks

(2020) Steven Galindo-Noreña et al.   Applied Sciences-Basel

A novel method for classification of BCI multi-class motor imagery task based on Dempster–Shafer theory

(2019) Sara Razi et al.   INFORMATION SCIENCES

Space-time recurrences for functional connectivity evaluation and feature extraction in motor imagery brain-computer interfaces

(2019) Paula G. Rodrigues et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

EEG Artifacts Handling in a Real Practical Brain–Computer Interface Controlled Vehicle

(2019) Aysa Jafarifarmand et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

A novel hybrid deep learning scheme for four-class motor imagery classification

(2019) Zhang Ruilong et al.   Journal of Neural Engineering

Brain wave classification using long short-term memory network based OPTICAL predictor

(2019) Shiu Kumar et al.   Scientific Reports

Correlation-based channel selection and regularized feature optimization for MI-based BCI

(2019) Jing Jin et al.   NEURAL NETWORKS

A comparison between power spectral density and network metrics: An EEG study

(2019) Matteo Demuru et al.   Biomedical Signal Processing and Control

Deep Learning for EEG motor imagery classification based on multi-layer CNNs feature fusion

(2019) Syed Umar Amin et al.   Future Generation Computer Systems-The International Journal of eScience

Can graph metrics be used for EEG-BCIs based on hand motor imagery?

(2018) Carlos Alberto Stefano Filho et al.   Biomedical Signal Processing and Control

Towards a Hybrid BCI Gaming Paradigm Based on Motor Imagery and SSVEP

(2018) Zhihua Wang et al.   INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION

EEGNet: a compact convolutional neural network for EEG-based brain--computer interfaces

(2018) Vernon Lawhern et al.   Journal of Neural Engineering

Towards BCI-actuated smart wheelchair system

(2018) Jingsheng Tang et al.   Biomedical Engineering Online

EEG datasets for motor imagery brain–computer interface

(2017) Hohyun Cho et al.   GigaScience

Facilitating Effects of Transcranial Direct Current Stimulation on Motor Imagery Brain-Computer Interface With Robotic Feedback for Stroke Rehabilitation

(2015) Kai Keng Ang et al.   ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION

Motor execution and motor imagery: A comparison of functional connectivity patterns based on graph theory

(2013) L. Xu et al.   NEUROSCIENCE

Brain-computer interfaces: military, neurosurgical, and ethical perspective

(2011) Ivan S. Kotchetkov et al.   Neurosurgical Focus