SynthSleepNet

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

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

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

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

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

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

ECG arrhythmia classification using a 2-D convolutional neural network

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 (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.

A Collection Python EEG (+ ECG) Analysis Utilities for OpenBCI and Muse