EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
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Updated
May 20, 2024 - Python
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".
Attention temporal convolutional network for EEG-based motor imagery classification
The decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting. (IEEE Sensors Journal)
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.
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.
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.
Towards Domain Free Transformer for Generalized EEG Pre-training
The codes that I implemented during my B.Sc. project.
Implementation of Convolutional Recurrent Neural Network (CRNN) to decode motor imagery EEG data.
University MS Thesis Project, Controlling an avatar in a Virtual Environment via EEG Motor Imagery
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.
Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking
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.
Official code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper
Code accompanying the publication "Guiding Soft Robots with Motor-Imagery Brain Signals and Impedance Control" that received the Best Paper Award at the RoboSoft 2024.
PyTorch code for "Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training"
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