Electroencephalography (EEG) is a non-invasive method for recording electrical activity in the brain, first performed on humans by Hans Berger in 1924 (Berger, 1929).
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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
Not supported. Measure 8 EEG channels with Shield PiEEG and RaspberryPi in C library
Deep learning software to decode EEG, ECG or MEG signals
Mother of All BCI Benchmarks
A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
Wearable (BLE) Brain-Computer Interface, ADS1299 and STM32 with SDK for mobile application
A unified multi-task time series model.
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
Parameterizing neural power spectra into periodic & aperiodic components.
A Python Toolbox for Statistics and Neurophysiological Signal Processing (EEG, EDA, ECG, EMG...).
Outdated, see new https://github.com/braindecode/braindecode
AntroPy: entropy and complexity of (EEG) time-series 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 (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.