eeg-signals-processing

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Not supported. Measure 8 EEG channels with Shield PiEEG and RaspberryPi in C library

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

Wearable (BLE) Brain-Computer Interface, ADS1299 and STM32 with SDK for mobile application

Variational mode decomposition (VMD) in Python

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.

A Python library for signal decomposition algorithms

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

Empirical wavelet transform (EWT) in Python

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 models(reproduction and experiments).

A python package for extracting EEG features. See article "Unsupervised EEG Artifact Detection and Correction" in Frontiers in Digital Health, 2020.

Analyze and manipulate EEG data using PyEEGLab.

EEG-Based Emotion Recognition

A driver, parser and real time brainwave plotter for NeuroSky MindWave EEG headset

An open source tool for large-scale EEG datasets processing

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

A set of tools to analyze and create charts from Muse EEG devices.

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

The official implement of Mind's eye: image recognition by EEG via multimodal similarity-keeping contrastive learning.