eeg-signals

Ildaron/ironbci

Open-Source Brain-Computer Interface, ADS1299 and STM32

raphaelvallat/yasa

YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.

neurotech-berkeley/neurotech-course

CS198-96: Intro to Neurotechnology @ UC Berkeley

SuperBruceJia/EEG-Motor-Imagery-Classification-CNNs-TensorFlow

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

MikeWangWZHL/EEG-To-Text

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

neerajwagh/eeg-gcnn

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

ufvceiec/EEGRAPH

EEGraph: Convert EEGs to graphs with frequency and time-frequency domain connectivity measures.

craddm/eegUtils

An R package for processing and plotting of electroencephalography (EEG) data

amrzhd/EEGNet

This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.

amrzhd/EEG-MSCNN

This project explores the impact of Multi-Scale CNNs on the classification of EEG signals in Brain-Computer Interface (BCI) systems. By comparing the performance of two models, EEGNet and MSTANN, the study demonstrates how richer temporal feature extractions can enhance CNN models in classifying EEG signals

MultiScale-BCI/IV-2a

nikk-nikaznan/SSVEP-Neural-Generative-Models

Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification

dolphin-in-a-coma/multi-task-cnn-eeg-emotion

Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.

Mentalab-hub/explorepy

Python API for Mentalab biosignal aquisition devices

ycq091044/ContraWR

JMIR AI'23: EEG dataset processing and EEG Self-supervised Learning

duanyiqun/DS-DDPM

Implementation of Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics/EEG Signals

mkfzdmr/Deep-Learning-based-Emotion-Recognition

Emotion Recognition, EEG Mapping, Azimuthal Projection Technique, CNN

nikk-nikaznan/Subject-Invariant-SSVEP-GAN

Code to accompany our International Conference on Pattern Recognition (ICPR) paper entitled - Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.

arkanivasarkar/EEG-Data-Augmentation-using-Variational-Autoencoder

Improving performance of motor imagery classification using variational-autoencoder and synthetic EEG signals

AliAmini93/ADHDeepNet

ADHDeepNet is a model that integrates temporal and spatial characterization, attention modules, and explainability techniques, optimized for EEG data ADAD diagnosis. Neural Architecture Search (NAS), Hyper-parameter optimization, and data augmentation are also incorporated to enhance the model's performance and accuracy.

BrainDynamicsUSYD/nftsim

C++ library for simulation of multiscale neural field dynamics

gist-ailab/IITNet-official

This is an official implementation for "Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG".

Ildaron/3.eeg_recognation

Machine learning for Anonymous detection of an alcoholic by EEG signals

SuperBruceJia/EEG-BayesianCNN

This is an EEG Signals Classification based on Bayesian Convolutional Neural Network (Bayesian CNNs) via Variational Inference.

IoBT-VISTEC/EEGANet

EEG Artifact Removal Using Deep Learning (source code, IEEE Journal of Biomedical and Health Informatics)

Nikeshbajaj/spkit

Signal Processing Toolkit, including ML models with visualization

geopopos/EEG_convolutional_neural_net

A convolutional neural network developed in python using the Keras machine learning framework used to categorize brain signal based on what a user was looking at when the EEG data was collected.

Pi-EEG/EEG-BCI-signal-processing

Real-time EEG BCI signal processing by Python

Amir-Hofo/EEGNet_Pytorch

This code implements the EEG Net deep learning model using PyTorch. The EEG Net model is based on the research paper titled "EEGNet: A Compact Convolutional Neural Network for EEG-based Brain-Computer Interfaces".

bnicenboim/eeguana

A package for manipulating EEG data in R.

MexsonFernandes/EEG-controlled-Robot-using-Neurosky-Mindwave-Mobile2

Mobile Robot controlled using Neurosky Mindwave headset. This repository contains the data collection and robot control scripts developed using C#. Features of the data has been extracted using EMD and HHT formulaes.

neerajwagh/eeg-self-supervision

Resources for the paper titled "Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability". Accepted at ML4H Symposium 2021 with an oral spotlight!

bruAristimunha/Re-Deep-Convolution-Neural-Network-and-Autoencoders-Based-Unsupervised-Feature-Learning-of-EEG

KonstantinosBarmpas/Advanced-Machine-Learning-Projects

[ETH Zurich] My projects for the module "Advanced Machine Learning" at ETH Zürich (Swiss Federal Institute of Technology in Zurich) during the academic year 2019-2020.

Pooria90/EEG-Motor-Imagery-Analysis

The codes that I implemented during my B.Sc. project.