This repository contains all the code used in the experiments of the paper Restricted Exhaustive Search for Frequency Band Selection in Motor Imagery Classification as well as additional information of the experiments and results, and how to reproduce them.

A display for training phase for motor imagery-based BCI (MI-based BCI) training using pygame.

In AugmentBrain we investigate the performance of different data augmentation methods for the classification of Motor Imagery (MI) data using a Convolutional Neural Network tailored for EEG named EEGNet.

Official code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper

The codes that I implemented during my B.Sc. project.

Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".

Implementation of Convolutional Recurrent Neural Network (CRNN) to decode motor imagery EEG data.

This is a python code for extracting EEG signals from dataset 2b from competition iv, then it converts the data to spectrogram images to classify them using a CNN classifier.

Neuroexon presents a hybrid-BCI system that utilizes motor imagery (MI) and steady-state visual-evoked potential (SSVEP) to control a one degree of freedom arm exoskeleton which provides the user with haptic feedback.

Towards Domain Free Transformer for Generalized EEG Pre-training

PyTorch code for "Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training"

Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

A trusted repository for groundbreaking EEG research code. Some peer-reviewed algorithms (such as EEG data augmentation techniques, EEG classification models) to push the boundaries of neuroscience.

Attention temporal convolutional network for EEG-based motor imagery classification

Functional connectivity and brain network analysis for motor imagery data in stroke patients

University MS Thesis Project, Controlling an avatar in a Virtual Environment via EEG Motor Imagery