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

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

Real-Time BCI for Rock-Paper-Scissors: Decoding Motor Imagery with Minimal Training

Exploring Brain Signal Processing Pipelines for Kaggle Challenges

A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning models(reproduction and experiments).

EEG Motor Imagery Classification Using CNN, Transformer, and MLP

Towards Domain Free Transformer for Generalized EEG Pre-training

Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence

EEG Classification API using Flask

Leveraging Transfer Learning to Improve Stroke Patient Motor-Imagery Classification.

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.

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

This code is for classifying spectrogram images of Motor Movement/Imagery tasks using a Convolutional Neural Network (CNN) and Generative Adversarial Network (GAN) for data augmentation..

This Python script creates, trains, and tests a Convolutional Neural Network (CNN) for image classification using various libraries like Numpy, Tensorflow, OpenCV, Keras, etc. The input images are spectrum images that are loaded from a specified folder path and pre-processed by resizing and normalizing.

Record EEG data from a Muse 2 headband using the MInd Monitor app and python osc module. Build and train a CNN model in Keras framework to classify Left-Right Motor Imagery. Make real-time predictions using the trained model.

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Using Deep Learning techniques to classify Motor Imagery Electroencephalography (EEG) signals

Rethinking CNN Architecture for Enhancing Decoding Performance of Motor Imagery-based EEG Signals

A MATLAB toolbox for classification of motor imagery tasks in EEG-based BCI system with CSP, FB-CSP and BSSFO

Motor Imagery in VR-BCI