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41 search results found

Mne Python ⭐ 2,449

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Pyriemann ⭐ 574

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

Mother of All BCI Benchmarks

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

Recursos Neuro ⭐ 215

Repositorio con recursos de Neurociencia Cognitiva y computacional con amplitud temática.

Antropy ⭐ 203

AntroPy: entropy and complexity of (EEG) time-series in Python

Deepeeg ⭐ 180

Deep Learning with Tensor Flow for EEG MNE Epoch Objects

Mne Cpp ⭐ 143

MNE-CPP: A Framework for Electrophysiology

Ai Nlp Paper Readings ⭐ 107

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

📊 EEG signal processing and machine learning in JavaScript

Deep Learning For Bci ⭐ 78

Resources for Book: Deep Learning for EEG-based Brain-Computer Interface: Representations, Algorithms and Applications

Machine Learning Course Projects ⭐ 68

Including some machine learning and artificial intellegent examples

MSc thesis on: Classifying brain activity using EEG and automated time tracking of computer use (using ActivityWatch)

Eeg Gcnn ⭐ 56

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.

Pymindaffectbci ⭐ 55

Python SDK for high performance on-line Brain Computer Interface development.

Awesome Healthmetrics ⭐ 52

A curated list of awesome resources at the intersection of healthcare and AI

Kaggle Eeg ⭐ 49

Seizure prediction from EEG data using machine learning. 3rd place solution for Kaggle/Uni Melbourne seizure prediction competition.

Bci_toolbox ⭐ 29

Classification toolbox for ERP and SSVEP based BCI data

Motor Imagery Tasks Classification Using Eeg Data ⭐ 29

Implementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data

Fbcsp Python ⭐ 25

Python implemementation of the FBCSP algorithm

Eeg Based Emotion Analysis Using Deap Dataset For Supervised Machine Learning ⭐ 25

This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.

An easy to use decoding toolbox for Matlab users.

Neuroml2020 ⭐ 20

Machine Learning in Neuroimaging data, Fall 2020.

Easylearn_dev ⭐ 20

Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatri

Eeg Emotions ⭐ 18

Application prepares data to learning process. Including preprocessing, cleaning, reformating, feature extraction using PyEEG library and learning using Sklearn tool.

End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)

Multi Task Cnn Eeg Emotion ⭐ 17

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

Eeg Self Supervision ⭐ 15

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!

Eeg_convolutional_neural_net ⭐ 12

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.

BEIRA: BOLD from EEG Interpretable Regression Autoencoder. Prediction subcortical BOLD activity from EEG data

Pyeegpipeline ⭐ 10

A complete pipeline for reading preprocessing and classification of EEG data using different statistical ML models and different deep Learning models

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

Brain Computer Interface Cybathlon2020 ⭐ 7

Master thesis subject: Leveraging Deep Learning for Real-time EEG Classification at Cybathlon's BCI-race

Eeg_signalsclassification ⭐ 7

Preprocessing, analysis and classification of EEG signals into 4 classes.

Machine Learning Portfolio ⭐ 7

Assorted machine learning implementations for medical data

🧠 ∿ 🔓 A file-storage application with ultra-mega-secure authentication using brain biometrics.

3.eeg_recognation ⭐ 6

Python (deep learning and machine learning) for EEG signal processing on the example of recognizing the disease of alcoholism

Interpretable Eeg Seizure Prediction Using A Multiobjective Evolutionary Algorithm ⭐ 6

Code and data of the paper "Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm", published by Scientific Reports in 2022.

Eegwavenet ⭐ 6

source codes for EEGWaveNet: Multi-Scale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection (IEEE Transactions on Industrial Informatics)

Biomedical Imaging ⭐ 5

Many-in-one repo: The "MNIST" of Brain Digits - Thought classification, Motor movement classification, 3D cancer detection, and Covid detection

Real Time Emotion Recognition From Eeg Signals Using One Electrode Device ⭐ 5

REAL-TIME EMOTION RECOGNITION FROM EEG SIGNALS USING ONE ELECTRODE DEVICE

Gcn_for_eeg ⭐ 5

Graph Convolutional Networks for 4-class EEG Classification

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