BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
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Updated
Nov 24, 2024 - C++
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
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf
Muse 2016 EEG Headset JavaScript Library (using Web Bluetooth)
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
The programming interface for your body and mind
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
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
A MATLAB package for modelling multivariate stimulus-response data
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
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."
🧠 Brain-Computer Interfacing bootcamp course + projects @ Saturdays.AI (BCI + AI)
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