An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
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Updated
Feb 27, 2024 - C
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Attention temporal convolutional network for EEG-based motor imagery classification
Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".
Matlab source code of the paper "D. Wu, X. Jiang, R. Peng, W. Kong, J. Huang and Z. Zeng, Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline, Information Sciences, 2021, submitted."
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).
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces (MEKT)
Motor Imagery EEG Signal Classification Using Random Subspace Ensemble Network
Official code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper
The decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting. (IEEE Sensors Journal)
Implementation of filter bank common spatial pattern (FBCSP) for MI-based BCI in python
A basic demonstration how to use Python, MNE, and PyTorch to analyze EEG signal.
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.
EEG BCI Real-Time Applications: Contains real-time demonstrations of BCI applications
The codes that I implemented during my B.Sc. project.
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
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.
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.
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