Code for paper "Application of Convolutional Neural Networks to Four-Class Motor Imagery Classification Problem"
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Updated
Aug 31, 2017 - MATLAB
Code for paper "Application of Convolutional Neural Networks to Four-Class Motor Imagery Classification Problem"
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.
Project to test the accuracy of multiple algorithms published in articles to the EEG binary motor imagery problem
OpenViBE BCI paradigm for controlling a drone
A display for training phase for motor imagery-based BCI (MI-based BCI) training using pygame.
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces (MEKT)
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.
Motor Imagery System Using a Low-Cost EEG Brain Computer Interface.
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.
Using Deep Learning techniques to classify Motor Imagery Electroencephalography (EEG) signals
A basic demonstration how to use Python, MNE, and PyTorch to analyze EEG signal.
Application to collect eeg data, analyze, and decode motor imagery classes in real time.
Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".
EEG BCI Real-Time Applications: Contains real-time demonstrations of BCI applications
This repo contains the code for my Bachelor-Thesis: Feature engineering for motor imagery classification.
Implementation of Convolutional Recurrent Neural Network (CRNN) to decode motor imagery EEG data.
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