There are 42 repositories under brain-computer-interface topic.
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
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
Mother of All BCI Benchmarks
[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
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
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
Low Cost Electroencephalogram Based Brain-Computer-Interface
Implementation of ConvLSTM in pytorch applied for BCI (Brain Machine Interface) following paper: Convolutional LSTM Network-A Machine Learning Approach for Precipitation Nowcasting
A wheelchair controlled by EEG brain signals and enhanced with assisted driving
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
A MATLAB package for modelling multivariate stimulus-response data
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
Python SDK for high performance on-line Brain Computer Interface development.
Riemannian Geometry workshop at vBCI Meeting 2021
Blackrock Microsystems Cerebus Link for Neural Signal Processing
Classification toolbox for ERP and SSVEP based BCI data
Deep Learning pipeline for motor-imagery classification.
Android SDK for the NeuroSky MindWave Mobile Brainwave Sensing Headset
🧠Brain-Computer Interfacing bootcamp course + projects @ Saturdays.AI (BCI + AI)
Python API for Mentalab biosignal aquisition devices
A simple closed-loop BCI simulator for testing real-time neural decoding algorithms
Documentation for Reproducing & Using the OpenBCI cEEGrid Adapter
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.
Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder (IEEE Access)
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification