Maxim Entropy based Common Spatial Pattern
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Updated
Aug 21, 2017 - MATLAB
Maxim Entropy based Common Spatial Pattern
Motor Imagery model for Technology Workshop class
Fuzzy Discernibility Matrix-based a novel feature selection technique
Exploring Brain Signal Processing Pipelines for Kaggle Challenges
Project for XAI606(Korea University)
Leveraging Transfer Learning to Improve Stroke Patient Motor-Imagery Classification.
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
Motor Imagery in VR-BCI
Real-Time BCI for Rock-Paper-Scissors: Decoding Motor Imagery with Minimal Training
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)
This project aim is to classify the motor imagery signals extracted from the brain using an Electro Encephalogram
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 MATLAB toolbox for classification of motor imagery tasks in EEG-based BCI system with CSP, FB-CSP and BSSFO
EEG Classification API using Flask
Motor Imagery System Using a Low-Cost EEG Brain Computer Interface.
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.
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
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