Trending repositories for topic brain-computer-interface
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
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
A driver, parser and real time brainwave plotter for NeuroSky MindWave EEG headset
A wheelchair controlled by EEG brain signals and enhanced with assisted driving
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
Documentation for Reproducing & Using the OpenBCI cEEGrid Adapter
A driver, parser and real time brainwave plotter for NeuroSky MindWave EEG headset
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
A wheelchair controlled by EEG brain signals and enhanced with assisted driving
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
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
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
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Implementation of "From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking"
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification
A MATLAB package for modelling multivariate stimulus-response data
Low Cost Electroencephalogram Based Brain-Computer-Interface
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
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 ...
Implementation of ConvLSTM in pytorch applied for BCI (Brain Machine Interface) following paper: Convolutional LSTM Network-A Machine Learning Approach for Precipitation Nowcasting
List of summer schools to study brain-computer interfaces, neurotechnology & related fields worldwide
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification
List of summer schools to study brain-computer interfaces, neurotechnology & related fields worldwide
Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Documentation for Reproducing & Using the OpenBCI cEEGrid Adapter
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
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.
Implementation of ConvLSTM in pytorch applied for BCI (Brain Machine Interface) following paper: Convolutional LSTM Network-A Machine Learning Approach for Precipitation Nowcasting
A simple closed-loop BCI simulator for testing real-time neural decoding algorithms
Official code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
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
Low Cost Electroencephalogram Based Brain-Computer-Interface
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)