Popular GitHub Repositories for Brain Computer Interface

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and a limited number of EEG channels. Paper: https://doi.org/10.1088/1741-2552/ac4430

Python Brain-Computer Interface Software

Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification

Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder (IEEE Access)

Implementation of "From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking"

Neural networks for EEG-MEG decoding with MNE-python and Tensorflow.

Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free user-independent solution, desirable for clinical diagnostics. A stepping stone for an objective assessment of glaucoma patients’ visual field.

EEG Motor Imagery with Deep Learning

Code for "General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data"

Network Designed to Eventually Yield Sentience and Sapience

A Starter Pack Into Getting, Learning and Making BCIs

This work aims to classify the occurrence of a feedback error, i.e., the perception of an error by a user interacting with a Brain-Computer Interface (BCI). To achieve that, Convolutional Neural Network (CNN) models are developed.

Python Jupyter notebook for Neuralink Patent No. US 2021/0012909 A1, titled "Real-Time Neural Spike Detection"

NeuroFlex: Feasibility of EEG-Based Motor Imagery Control of a Soft Glove for Hand Rehabilitation