There are 6 repositories under motor-imagery-classification topic.
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
Deep Learning pipeline for motor-imagery classification.
Improving performance of motor imagery classification using variational-autoencoder and synthetic EEG signals
Rethinking CNN Architecture for Enhancing Decoding Performance of Motor Imagery-based EEG Signals
Motor Imagery EEG signal Classification on DWT
Project to test the accuracy of multiple algorithms published in articles to the EEG binary motor imagery problem
Towards Domain Free Transformer for Generalized EEG Pre-training
EEG Motor Imagery Classification Using CNN, Transformer, and MLP
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.
Senior Design Project at UH
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..
Using Deep Learning techniques to classify Motor Imagery Electroencephalography (EEG) signals
Motor Imagery System Using a Low-Cost EEG Brain Computer Interface.
EEG Classification API using Flask
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 MATLAB toolbox for classification of motor imagery tasks in EEG-based BCI system with CSP, FB-CSP and BSSFO
This project aim is to classify the motor imagery signals extracted from the brain using an Electro Encephalogram
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.
ECoG Motor Imagery Classification and Analysis. (Neuromatch Academy Project)
Orthogonal matching pursuit-based feature selection for motor-imagery EEG signal
University MS Thesis Project, Controlling an avatar in a Virtual Environment via EEG Motor Imagery
Project for XAI606(Korea University)
Leveraging Transfer Learning to Improve Stroke Patient Motor-Imagery Classification.
Repository used to test several preprocessing/classification pipelines on brain signals (EEG/EMG/MEG datasets).
Real-Time BCI for Rock-Paper-Scissors: Decoding Motor Imagery with Minimal Training
Motor Imagery in VR-BCI
Fuzzy Discernibility Matrix-based a novel feature selection technique
Maxim Entropy based Common Spatial Pattern
Motor Imagery model for Technology Workshop class