Trending repositories for topic eeg
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
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
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
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...
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
A list of openly available datasets in (mostly human) electrophysiology.
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
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...
MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
A list of openly available datasets in (mostly human) electrophysiology.
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
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
Deep learning software to decode EEG, ECG or MEG signals
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
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
A curated list of awesome neuroscience libraries, software and any content related to the domain.
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
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...
A list of openly available datasets in (mostly human) electrophysiology.
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
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...
Deep learning software to decode EEG, ECG or MEG signals
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
A list of openly available datasets in (mostly human) electrophysiology.
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel 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
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
BioAmp EXG Pill is a small and elegant Analog Front End (AFE) board for BioPotential signal acquisition.
Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electrophysiology
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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
Deep learning software to decode EEG, ECG or MEG signals
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
Attention temporal convolutional network for EEG-based motor imagery classification
EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
A curated list of awesome neuroscience libraries, software and any content related to the domain.
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
A list of openly available datasets in (mostly human) electrophysiology.
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
Not supported. Measure 8 EEG channels with Shield PiEEG and RaspberryPi in C library
Textbook for NESC 3505, Neural Data Science, at Dalhousie University
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...
NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semanti...
A Convolutional Transformer to decode mental states from Electroencephalography (EEG) for Brain-Computer Interfaces (BCI)
Local-first behavior tracking and brain recording app. Discord: https://discord.gg/sqsuzXWE3K
GGN model for seizure classification (datasets: TUH EEG seizure TUSZ 1.5.2)
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.
selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data
Attention temporal convolutional network for EEG-based motor imagery classification
Brainconn - an R package for visualising brain connectivity data in 2D and interactive 3D
Textbook for NESC 3505, Neural Data Science, at Dalhousie University
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
Scripts to a) download DEAP EEG dataset b) preprocess its EEG signals and c) perform feature extraction
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
source codes for EEGWaveNet: Multi-Scale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection (IEEE Transactions on Industrial Informatics)
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
MSc thesis on: Classifying brain activity using EEG and automated time tracking of computer use (using ActivityWatch)
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
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...
Developed the Neuro Vision Transformer, an innovative machine learning model utilizing Vision Transformer architecture for EEG signal classification, focusing on distinguishing ADHD from healthy parti...
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Deep learning software to decode EEG, ECG or MEG signals
A curated list of awesome neuroscience libraries, software and any content related to the domain.
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
A list of openly available datasets in (mostly human) electrophysiology.
Not supported. Measure 8 EEG channels with Shield PiEEG and RaspberryPi in C library
Attention temporal convolutional network for EEG-based motor imagery classification
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
Resources for Book: Deep Learning for EEG-based Brain-Computer Interface: Representations, Algorithms and Applications
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning mode...
Local-first behavior tracking and brain recording app. Discord: https://discord.gg/sqsuzXWE3K
Scripts to a) download DEAP EEG dataset b) preprocess its EEG signals and c) perform feature extraction
GGN model for seizure classification (datasets: TUH EEG seizure TUSZ 1.5.2)
Attention temporal convolutional network for EEG-based motor imagery classification
[IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
Textbook for NESC 3505, Neural Data Science, at Dalhousie University
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Rethinking CNN Architecture for Enhancing Decoding Performance of Motor Imagery-based EEG Signals
Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.
Exploration of diffuison-based generative model to sychronizing brain dynamics from semantic language input.
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (c...
Resources for Book: Deep Learning for EEG-based Brain-Computer Interface: Representations, Algorithms and Applications