Trending repositories for topic eeg

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

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

🔧🧠 MEEGkit: MEG & EEG processing toolkit in 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...

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

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

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...

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

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

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

A unified multi-task time series model.

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

Mother of All BCI Benchmarks

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...

A list of openly available datasets in (mostly human) electrophysiology.

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

EEG-based emotion classification using DEAP dataset

Deep learning software to decode EEG, ECG or MEG signals

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 curated list of awesome neuroscience libraries, software and any content related to the domain.

EEG Sleep stage classification using CNN with Keras

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python

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

Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electrophysiology

Open-Source Brain-Computer Interface, ADS1299 and STM32

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

The MATLAB toolbox for MEG, EEG and iEEG analysis

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

EEG-based emotion classification using DEAP dataset

A unified multi-task time series model.

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

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...

A list of openly available datasets in (mostly human) electrophysiology.

EEG Sleep stage classification using CNN with Keras

Mother of All BCI Benchmarks

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

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

Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electrophysiology

Deep learning software to decode EEG, ECG or MEG signals

Open-Source Brain-Computer Interface, ADS1299 and STM32

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

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

A curated list of awesome neuroscience libraries, software and any content related to the domain.

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

The MATLAB toolbox for MEG, EEG and iEEG analysis

A unified multi-task time series model.

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

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

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

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 list of openly available datasets in (mostly human) electrophysiology.

Mother of All BCI Benchmarks

A curated list of awesome neuroscience libraries, software and any content related to the domain.

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

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

Open-Source board for converting RaspberryPI to Brain-computer interface

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...

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

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

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

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

selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data

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

selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data

[IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"

A unified multi-task time series model.

Use DNNs to build encoding models of EEG visual responses.

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...

Simulation and optimization of neural circuits for MEG/EEG source estimates

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

Scripts to a) download DEAP EEG dataset b) preprocess its EEG signals and c) perform feature extraction

A list of openly available datasets in (mostly human) electrophysiology.

EEG-based emotion classification using DEAP dataset

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...

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

EEG Sleep stage classification using CNN with Keras

SPM (Statistical Parametric Mapping) - Development Version

Repository for the hmp python package

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

This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) applications.

BioAmp EXG Pill is a small and elegant Analog Front End (AFE) board for BioPotential signal acquisition.

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python

A unified multi-task time series model.

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

selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

A unified multi-task time series model.

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

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.

Deep learning software to decode EEG, ECG or MEG signals

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

A curated list of awesome neuroscience libraries, software and any content related to the domain.

Open-Source board for converting RaspberryPI to Brain-computer interface

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"

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

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

Attention temporal convolutional network for EEG-based motor imagery classification

A list of openly available datasets in (mostly human) electrophysiology.

The MATLAB toolbox for MEG, EEG and iEEG analysis

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

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

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

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...

Exploration of diffuison-based generative model to sychronizing brain dynamics from semantic language input.

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

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

SPM (Statistical Parametric Mapping) - Development Version

Analysis of Transformer attention in EEG signal classification

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

Scripts to a) download DEAP EEG dataset b) preprocess its EEG signals and c) perform feature extraction

Artifact Subspace Reconstruction for 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...

Textbook for NESC 3505, Neural Data Science, at Dalhousie University

Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

Use DNNs to build encoding models of EEG visual responses.

Repository for the hmp python package

Multimodal Dataset of Freezing of Gait in Parkinson's Disease

Simulation and optimization of neural circuits for MEG/EEG source estimates

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

A multitaper spectral estimation toolbox implemented in Matlab, Python, and R